Confidence Intervals
Risk Factors
Odds Ratio
The ratio of two odds. The exposure-odds ratio for case control data is the ratio of the odds in favor of exposure among cases to the odds in favor of exposure among noncases. The disease-odds ratio for a cohort or cross section is the ratio of the odds in favor of disease among the exposed to the odds in favor of disease among the unexposed. The prevalence-odds ratio refers to an odds ratio derived cross-sectionally from studies of prevalent cases.
Case-Control Studies
Studies which start with the identification of persons with a disease of interest and a control (comparison, referent) group without the disease. The relationship of an attribute to the disease is examined by comparing diseased and non-diseased persons with regard to the frequency or levels of the attribute in each group.
Cohort Studies
Studies in which subsets of a defined population are identified. These groups may or may not be exposed to factors hypothesized to influence the probability of the occurrence of a particular disease or other outcome. Cohorts are defined populations which, as a whole, are followed in an attempt to determine distinguishing subgroup characteristics.
Prospective Studies
Incidence
Follow-Up Studies
Logistic Models
Statistical models which describe the relationship between a qualitative dependent variable (that is, one which can take only certain discrete values, such as the presence or absence of a disease) and an independent variable. A common application is in epidemiology for estimating an individual's risk (probability of a disease) as a function of a given risk factor.
Treatment Outcome
Retrospective Studies
Studies used to test etiologic hypotheses in which inferences about an exposure to putative causal factors are derived from data relating to characteristics of persons under study or to events or experiences in their past. The essential feature is that some of the persons under study have the disease or outcome of interest and their characteristics are compared with those of unaffected persons.
Proportional Hazards Models
Risk
Multivariate Analysis
Risk Assessment
Prevalence
Age Factors
Age as a constituent element or influence contributing to the production of a result. It may be applicable to the cause or the effect of a circumstance. It is used with human or animal concepts but should be differentiated from AGING, a physiological process, and TIME FACTORS which refers only to the passage of time.
Cross-Sectional Studies
Prognosis
Pregnancy
Questionnaires
Predictive Value of Tests
In screening and diagnostic tests, the probability that a person with a positive test is a true positive (i.e., has the disease), is referred to as the predictive value of a positive test; whereas, the predictive value of a negative test is the probability that the person with a negative test does not have the disease. Predictive value is related to the sensitivity and specificity of the test.
Survival Analysis
A class of statistical procedures for estimating the survival function (function of time, starting with a population 100% well at a given time and providing the percentage of the population still well at later times). The survival analysis is then used for making inferences about the effects of treatments, prognostic factors, exposures, and other covariates on the function.
Genotype
Randomized Controlled Trials as Topic
Genetic Predisposition to Disease
Registries
Regression Analysis
Procedures for finding the mathematical function which best describes the relationship between a dependent variable and one or more independent variables. In linear regression (see LINEAR MODELS) the relationship is constrained to be a straight line and LEAST-SQUARES ANALYSIS is used to determine the best fit. In logistic regression (see LOGISTIC MODELS) the dependent variable is qualitative rather than continuously variable and LIKELIHOOD FUNCTIONS are used to find the best relationship. In multiple regression, the dependent variable is considered to depend on more than a single independent variable.
Sex Factors
Maleness or femaleness as a constituent element or influence contributing to the production of a result. It may be applicable to the cause or effect of a circumstance. It is used with human or animal concepts but should be differentiated from SEX CHARACTERISTICS, anatomical or physiological manifestations of sex, and from SEX DISTRIBUTION, the number of males and females in given circumstances.
Survival Rate
Double-Blind Method
Kaplan-Meier Estimate
A nonparametric method of compiling LIFE TABLES or survival tables. It combines calculated probabilities of survival and estimates to allow for observations occurring beyond a measurement threshold, which are assumed to occur randomly. Time intervals are defined as ending each time an event occurs and are therefore unequal. (From Last, A Dictionary of Epidemiology, 1995)
Polymorphism, Genetic
The regular and simultaneous occurrence in a single interbreeding population of two or more discontinuous genotypes. The concept includes differences in genotypes ranging in size from a single nucleotide site (POLYMORPHISM, SINGLE NUCLEOTIDE) to large nucleotide sequences visible at a chromosomal level.
Sensitivity and Specificity
Longitudinal Studies
Chi-Square Distribution
A distribution in which a variable is distributed like the sum of the squares of any given independent random variable, each of which has a normal distribution with mean of zero and variance of one. The chi-square test is a statistical test based on comparison of a test statistic to a chi-square distribution. The oldest of these tests are used to detect whether two or more population distributions differ from one another.
Age Distribution
Confounding Factors (Epidemiology)
Factors that can cause or prevent the outcome of interest, are not intermediate variables, and are not associated with the factor(s) under investigation. They give rise to situations in which the effects of two processes are not separated, or the contribution of causal factors cannot be separated, or the measure of the effect of exposure or risk is distorted because of its association with other factors influencing the outcome of the study.
European Continental Ancestry Group
Polymorphism, Single Nucleotide
Reproducibility of Results
The statistical reproducibility of measurements (often in a clinical context), including the testing of instrumentation or techniques to obtain reproducible results. The concept includes reproducibility of physiological measurements, which may be used to develop rules to assess probability or prognosis, or response to a stimulus; reproducibility of occurrence of a condition; and reproducibility of experimental results.
Body Mass Index
An indicator of body density as determined by the relationship of BODY WEIGHT to BODY HEIGHT. BMI=weight (kg)/height squared (m2). BMI correlates with body fat (ADIPOSE TISSUE). Their relationship varies with age and gender. For adults, BMI falls into these categories: below 18.5 (underweight); 18.5-24.9 (normal); 25.0-29.9 (overweight); 30.0 and above (obese). (National Center for Health Statistics, Centers for Disease Control and Prevention)
Cause of Death
Sex Distribution
Myocardial Infarction
Socioeconomic Factors
Comorbidity
The presence of co-existing or additional diseases with reference to an initial diagnosis or with reference to the index condition that is the subject of study. Comorbidity may affect the ability of affected individuals to function and also their survival; it may be used as a prognostic indicator for length of hospital stay, cost factors, and outcome or survival.
Biological Markers
Measurable and quantifiable biological parameters (e.g., specific enzyme concentration, specific hormone concentration, specific gene phenotype distribution in a population, presence of biological substances) which serve as indices for health- and physiology-related assessments, such as disease risk, psychiatric disorders, environmental exposure and its effects, disease diagnosis, metabolic processes, substance abuse, pregnancy, cell line development, epidemiologic studies, etc.
Cardiovascular Diseases
HIV Infections
Drug Administration Schedule
Population Surveillance
Linear Models
Occupational Exposure
Stroke
A group of pathological conditions characterized by sudden, non-convulsive loss of neurological function due to BRAIN ISCHEMIA or INTRACRANIAL HEMORRHAGES. Stroke is classified by the type of tissue NECROSIS, such as the anatomic location, vasculature involved, etiology, age of the affected individual, and hemorrhagic vs. non-hemorrhagic nature. (From Adams et al., Principles of Neurology, 6th ed, pp777-810)
Disease Progression
Colorectal Neoplasms
Severity of Illness Index
Asian Continental Ancestry Group
Epidemiologic Methods
Environmental Exposure
Electrocardiography
Recording of the moment-to-moment electromotive forces of the HEART as projected onto various sites on the body's surface, delineated as a scalar function of time. The recording is monitored by a tracing on slow moving chart paper or by observing it on a cardioscope, which is a CATHODE RAY TUBE DISPLAY.
Drug Therapy, Combination
ROC Curve
Neoplasms
African Americans
Alcohol Drinking
Analysis of Variance
Health Surveys
Parity
Mass Screening
Alleles
Netherlands
Neoplasm Staging
Hospital Mortality
Coronary Disease
Disease-Free Survival
Cross-Over Studies
Studies comparing two or more treatments or interventions in which the subjects or patients, upon completion of the course of one treatment, are switched to another. In the case of two treatments, A and B, half the subjects are randomly allocated to receive these in the order A, B and half to receive them in the order B, A. A criticism of this design is that effects of the first treatment may carry over into the period when the second is given. (Last, A Dictionary of Epidemiology, 2d ed)
African Continental Ancestry Group
Treatment Failure
Hypertension
Chronic Disease
Diseases which have one or more of the following characteristics: they are permanent, leave residual disability, are caused by nonreversible pathological alteration, require special training of the patient for rehabilitation, or may be expected to require a long period of supervision, observation, or care. (Dictionary of Health Services Management, 2d ed)
Gene Frequency
Antineoplastic Combined Chemotherapy Protocols
Reference Values
Obesity
A status with BODY WEIGHT that is grossly above the acceptable or desirable weight, usually due to accumulation of excess FATS in the body. The standards may vary with age, sex, genetic or cultural background. In the BODY MASS INDEX, a BMI greater than 30.0 kg/m2 is considered obese, and a BMI greater than 40.0 kg/m2 is considered morbidly obese (MORBID OBESITY).
Models, Statistical
Ethnic Groups
Databases, Factual
Extensive collections, reputedly complete, of facts and data garnered from material of a specialized subject area and made available for analysis and application. The collection can be automated by various contemporary methods for retrieval. The concept should be differentiated from DATABASES, BIBLIOGRAPHIC which is restricted to collections of bibliographic references.
Postoperative Complications
Postmenopause
Single-Blind Method
Pregnancy Outcome
Poisson Distribution
Haplotypes
France
Heart Failure
A heterogeneous condition in which the heart is unable to pump out sufficient blood to meet the metabolic need of the body. Heart failure can be caused by structural defects, functional abnormalities (VENTRICULAR DYSFUNCTION), or a sudden overload beyond its capacity. Chronic heart failure is more common than acute heart failure which results from sudden insult to cardiac function, such as MYOCARDIAL INFARCTION.
Outcome Assessment (Health Care)
Spain
Dose-Response Relationship, Drug
Diabetes Mellitus
Statistics, Nonparametric
A class of statistical methods applicable to a large set of probability distributions used to test for correlation, location, independence, etc. In most nonparametric statistical tests, the original scores or observations are replaced by another variable containing less information. An important class of nonparametric tests employs the ordinal properties of the data. Another class of tests uses information about whether an observation is above or below some fixed value such as the median, and a third class is based on the frequency of the occurrence of runs in the data. (From McGraw-Hill Dictionary of Scientific and Technical Terms, 4th ed, p1284; Corsini, Concise Encyclopedia of Psychology, 1987, p764-5)
Canada
Publication Bias
The influence of study results on the chances of publication and the tendency of investigators, reviewers, and editors to submit or accept manuscripts for publication based on the direction or strength of the study findings. Publication bias has an impact on the interpretation of clinical trials and meta-analyses. Bias can be minimized by insistence by editors on high-quality research, thorough literature reviews, acknowledgement of conflicts of interest, modification of peer review practices, etc.
Birth Weight
Area Under Curve
A statistical means of summarizing information from a series of measurements on one individual. It is frequently used in clinical pharmacology where the AUC from serum levels can be interpreted as the total uptake of whatever has been administered. As a plot of the concentration of a drug against time, after a single dose of medicine, producing a standard shape curve, it is a means of comparing the bioavailability of the same drug made by different companies. (From Winslade, Dictionary of Clinical Research, 1992)
Coronary Artery Disease
Gestational Age
Aspirin
The prototypical analgesic used in the treatment of mild to moderate pain. It has anti-inflammatory and antipyretic properties and acts as an inhibitor of cyclooxygenase which results in the inhibition of the biosynthesis of prostaglandins. Aspirin also inhibits platelet aggregation and is used in the prevention of arterial and venous thrombosis. (From Martindale, The Extra Pharmacopoeia, 30th ed, p5)
Emergency Service, Hospital
Residence Characteristics
Bias (Epidemiology)
Any deviation of results or inferences from the truth, or processes leading to such deviation. Bias can result from several sources: one-sided or systematic variations in measurement from the true value (systematic error); flaws in study design; deviation of inferences, interpretations, or analyses based on flawed data or data collection; etc. There is no sense of prejudice or subjectivity implied in the assessment of bias under these conditions.
Life Style
Polymerase Chain Reaction
In vitro method for producing large amounts of specific DNA or RNA fragments of defined length and sequence from small amounts of short oligonucleotide flanking sequences (primers). The essential steps include thermal denaturation of the double-stranded target molecules, annealing of the primers to their complementary sequences, and extension of the annealed primers by enzymatic synthesis with DNA polymerase. The reaction is efficient, specific, and extremely sensitive. Uses for the reaction include disease diagnosis, detection of difficult-to-isolate pathogens, mutation analysis, genetic testing, DNA sequencing, and analyzing evolutionary relationships.
Data Interpretation, Statistical
Anti-Inflammatory Agents, Non-Steroidal
Anti-inflammatory agents that are non-steroidal in nature. In addition to anti-inflammatory actions, they have analgesic, antipyretic, and platelet-inhibitory actions.They act by blocking the synthesis of prostaglandins by inhibiting cyclooxygenase, which converts arachidonic acid to cyclic endoperoxides, precursors of prostaglandins. Inhibition of prostaglandin synthesis accounts for their analgesic, antipyretic, and platelet-inhibitory actions; other mechanisms may contribute to their anti-inflammatory effects.
Pregnancy Complications
Combined Modality Therapy
Asthma
Ontario
A province of Canada lying between the provinces of Manitoba and Quebec. Its capital is Toronto. It takes its name from Lake Ontario which is said to represent the Iroquois oniatariio, beautiful lake. (From Webster's New Geographical Dictionary, 1988, p892 & Room, Brewer's Dictionary of Names, 1992, p391)
Neoplasm Recurrence, Local
Health Status
Statistics as Topic
Social Class
Hispanic Americans
Age of Onset
Pilot Projects
Continental Population Groups
Infusions, Intravenous
Observer Variation
The failure by the observer to measure or identify a phenomenon accurately, which results in an error. Sources for this may be due to the observer's missing an abnormality, or to faulty technique resulting in incorrect test measurement, or to misinterpretation of the data. Two varieties are inter-observer variation (the amount observers vary from one another when reporting on the same material) and intra-observer variation (the amount one observer varies between observations when reporting more than once on the same material).
Diabetes Mellitus, Type 2
A subclass of DIABETES MELLITUS that is not INSULIN-responsive or dependent (NIDDM). It is characterized initially by INSULIN RESISTANCE and HYPERINSULINEMIA; and eventually by GLUCOSE INTOLERANCE; HYPERGLYCEMIA; and overt diabetes. Type II diabetes mellitus is no longer considered a disease exclusively found in adults. Patients seldom develop KETOSIS but often exhibit OBESITY.
Kidney Failure, Chronic
The end-stage of CHRONIC RENAL INSUFFICIENCY. It is characterized by the severe irreversible kidney damage (as measured by the level of PROTEINURIA) and the reduction in GLOMERULAR FILTRATION RATE to less than 15 ml per min (Kidney Foundation: Kidney Disease Outcome Quality Initiative, 2002). These patients generally require HEMODIALYSIS or KIDNEY TRANSPLANTATION.
Causality
The relating of causes to the effects they produce. Causes are termed necessary when they must always precede an effect and sufficient when they initiate or produce an effect. Any of several factors may be associated with the potential disease causation or outcome, including predisposing factors, enabling factors, precipitating factors, reinforcing factors, and risk factors.
Australia
Epidemiologic Studies
Atrial Fibrillation
Abnormal cardiac rhythm that is characterized by rapid, uncoordinated firing of electrical impulses in the upper chambers of the heart (HEART ATRIA). In such case, blood cannot be effectively pumped into the lower chambers of the heart (HEART VENTRICLES). It is caused by abnormal impulse generation.
Algorithms
Exercise
SEER Program
A cancer registry mandated under the National Cancer Act of 1971 to operate and maintain a population-based cancer reporting system, reporting periodically estimates of cancer incidence and mortality in the United States. The Surveillance, Epidemiology, and End Results (SEER) Program is a continuing project of the National Cancer Institute of the National Institutes of Health. Among its goals, in addition to assembling and reporting cancer statistics, are the monitoring of annual cancer incident trends and the promoting of studies designed to identify factors amenable to cancer control interventions. (From National Cancer Institute, NIH Publication No. 91-3074, October 1990)
Wounds and Injuries
Diabetes Complications
Placebos
Any dummy medication or treatment. Although placebos originally were medicinal preparations having no specific pharmacological activity against a targeted condition, the concept has been extended to include treatments or procedures, especially those administered to control groups in clinical trials in order to provide baseline measurements for the experimental protocol.
Carcinoma, Squamous Cell
Infant, Low Birth Weight
Contraceptives, Oral
Tumor Markers, Biological
Molecular products metabolized and secreted by neoplastic tissue and characterized biochemically in cells or body fluids. They are indicators of tumor stage and grade as well as useful for monitoring responses to treatment and predicting recurrence. Many chemical groups are represented including hormones, antigens, amino and nucleic acids, enzymes, polyamines, and specific cell membrane proteins and lipids.
Research Design
Seasons
New Zealand
A group of islands in the southwest Pacific. Its capital is Wellington. It was discovered by the Dutch explorer Abel Tasman in 1642 and circumnavigated by Cook in 1769. Colonized in 1840 by the New Zealand Company, it became a British crown colony in 1840 until 1907 when colonial status was terminated. New Zealand is a partly anglicized form of the original Dutch name Nieuw Zeeland, new sea land, possibly with reference to the Dutch province of Zeeland. (From Webster's New Geographical Dictionary, 1988, p842 & Room, Brewer's Dictionary of Names, 1992, p378)
Premature Birth
Likelihood Functions
Body mass decrease after initial gain following smoking cessation. (1/7400)
BACKGROUND: Although smoking cessation is strongly associated with subsequent weight gain, it is not clear whether the initial gain in weight after smoking cessation remains over time. METHOD: Cross-sectional analyses were made, using data from periodic health examinations for workers, on the relationship between body mass index (BMI) and the length of smoking cessation. In addition, linear regression coefficients of BMI on the length of cessation were estimated according to alcohol intake and sport activity, to examine the modifying effect of these factors on the weight of former smokers. RESULTS: Means of BMI were 23.1 kg/m2, 23.3 kg/m2, 23.6 kg/m2 for light/medium smokers, heavy smokers and never smokers, respectively. Among former smokers who had smoked > or = 25 cigarettes a day, odds ratio (OR) of BMI >25 kg/m2 were 1.88 (95% confidence interval [CI] : 1.05-3.35), 1.32 (95% CI : 0.74-2.34), 0.66 (95% CI: 0.33-1.31) for those with 2-4 years, 5-7 years, and 8-10 years of smoking cessation, respectively. The corresponding OR among those who previously consumed <25 cigarettes a day were 1.06 (95% CI: 0.58-1.94), 1.00 (95% CI: 0.58-1.71), and 1.49 (95% CI: 0.95-2.32). CONCLUSIONS: The results suggest that although heavy smokers may experience large weight gain and weigh more than never smokers in the few years after smoking cessation, they thereafter lose weight to the never smoker level, while light and moderate smokers gain weight up to the never smoker level without any excess after smoking cessation. (+info)Relation between obesity and breast cancer in young women. (2/7400)
This study was conducted to assess the relation between body size and risk of breast cancer among young women. A case-control study was conducted among women aged 21-45 years living in three counties in Washington State. Cases were women born after 1944 with invasive or in situ breast cancer that was diagnosed between January 1, 1983, and April 30, 1990. Controls were selected using random digit dialing and were frequency-matched to cases on the basis of age and county of residence. Interviews took place between 1986 and 1992. Body size was evaluated using indices from several different time periods. After adjustment for confounders, a decreased risk of breast cancer was found for women in the highest quintile of body mass index (weight (kg)/height (m)2) as compared with the lowest quintile (for maximum lifetime body mass index, odds ratio = 0.69, 95% confidence interval (CI) 0.51-0.94). Age modified the relation between body size and risk of breast cancer. The odds ratio for women in the highest quintile of maximum body mass index who were aged 21-35 years was 0.29 (95% CI 0.16-0.55), as compared with an odds ratio of 1.5 for women aged 36-45 years (95% CI 0.9-2.5) (p for interaction = 0.003). This study supports prior research showing a decreased risk of breast cancer associated with increased body size among premenopausal or young women. More detailed analysis in this study found a strong effect that was limited to the youngest age group (< or = 35 years). (+info)Risk factors for injuries and other health problems sustained in a marathon. (3/7400)
OBJECTIVES: To identify risk factors for injuries and other health problems occurring during or immediately after participation in a marathon. METHODS: A prospective cohort study was undertaken of participants in the 1993 Auckland Citibank marathon. Demographic data, information on running experience, training and injuries, and information on other lifestyle factors were obtained from participants before the race using an interviewer-administered questionnaire. Information on injuries and other health problems sustained during or immediately after the marathon were obtained by a self administered questionnaire. Logistic regression analyses were undertaken to identify significant risk factors for health problems. RESULTS: This study, one of only a few controlled epidemiological studies that have been undertaken of running injuries, has identified a number of risk factors for injuries and other health problems sustained in a marathon. Men were at increased risk of hamstring and calf problems, whereas women were at increased risk of hip problems. Participation in a marathon for the first time, participation in other sports, illness in the two weeks before the marathon, current use of medication, and drinking alcohol once a month or more, were associated with increased self reported risks of problems. While increased training seemed to increase the risk of front thigh and hamstring problems, it may decrease the risk of knee problems. There are significant but complex relations between age and risk of injury or health problem. CONCLUSIONS: This study has identified certain high risk subjects and risk factors for injuries and other health problems sustained in a marathon. In particular, subjects who have recently been unwell or are taking medication should weigh up carefully the pros and cons of participating. (+info)Statistical inference by confidence intervals: issues of interpretation and utilization. (4/7400)
This article examines the role of the confidence interval (CI) in statistical inference and its advantages over conventional hypothesis testing, particularly when data are applied in the context of clinical practice. A CI provides a range of population values with which a sample statistic is consistent at a given level of confidence (usually 95%). Conventional hypothesis testing serves to either reject or retain a null hypothesis. A CI, while also functioning as a hypothesis test, provides additional information on the variability of an observed sample statistic (ie, its precision) and on its probable relationship to the value of this statistic in the population from which the sample was drawn (ie, its accuracy). Thus, the CI focuses attention on the magnitude and the probability of a treatment or other effect. It thereby assists in determining the clinical usefulness and importance of, as well as the statistical significance of, findings. The CI is appropriate for both parametric and nonparametric analyses and for both individual studies and aggregated data in meta-analyses. It is recommended that, when inferential statistical analysis is performed, CIs should accompany point estimates and conventional hypothesis tests wherever possible. (+info)Where do people go for treatment of sexually transmitted diseases? (5/7400)
CONTEXT: Major public health resources are devoted to the prevention of sexually transmitted diseases (STDs) through public STD clinics. However, little is known about where people actually receive treatment for STDs. METHODS: As part of the National Health and Social Life Survey, household interviews were performed from February to September 1992 with 3,432 persons aged 18-59. Weighted population estimates and multinomial response methods were used to describe the prevalence of self-reported STDs and patterns of treatment utilization by persons who ever had a bacterial or viral STD. RESULTS: An estimated two million STDs were self-reported in the previous year, and 22 million 18-59-year-olds self-reported lifetime STDs. Bacterial STDs (gonorrhea, chlamydia, nongonococcal urethritis, pelvic inflammatory disease and syphilis) were more common than viral STDs (genital herpes, genital warts, hepatitis and HIV). Genital warts were the most commonly reported STD in the past year, while gonorrhea was the most common ever-reported STD. Almost half of all respondents who had ever had an STD had gone to a private practice for treatment (49%); in comparison, only 5% of respondents had sought treatment at an STD clinic. Respondents with a bacterial STD were seven times more likely to report going to an STD clinic than were respondents with a viral STD--except for chlamydia, which was more likely to be treated at family planning clinics. Men were significantly more likely than women to go to an STD clinic. Young, poor or black respondents were all more likely to use a family planning clinic for STD treatment than older, relatively wealthy or white respondents. Age, sexual history and geographic location did not predict particular types of treatment-seeking. CONCLUSIONS: The health care utilization patterns for STD treatment in the United States are complex. Specific disease diagnosis, gender, race and income status all affect where people will seek treatment. These factors need to be taken into account when STD prevention strategies are being developed. (+info)Condom use and HIV risk behaviors among U.S. adults: data from a national survey. (6/7400)
CONTEXT: How much condom use among U.S. adults varies by type of partner or by risk behavior is unclear. Knowledge of such differentials would aid in evaluating the progress being made toward goals for levels of condom use as part of the Healthy People 2000 initiative. METHODS: Data were analyzed from the 1996 National Household Survey of Drug Abuse, an annual household-based probability sample of the noninstitutionalized population aged 12 and older that measures the use of illicit drugs, alcohol and tobacco. The personal behaviors module included 25 questions covering sexual activity in the past year, frequency of condom use in the past year, circumstances of the last sexual encounter and HIV testing. RESULTS: Sixty-two percent of adults reported using a condom at last intercourse outside of an ongoing relationship, while only 19% reported using condoms when the most recent intercourse occurred within a steady relationship. Within ongoing relationships, condom use was highest among respondents who were younger, black, of lower income and from large metropolitan areas. Forty percent of unmarried adults used a condom at last sex, compared with the health objective of 50% for the year 2000. Forty percent of injecting drug users used condoms at last intercourse, compared with the 60% condom use objective for high-risk individuals. Significantly, persons at increased risk for HIV because of their sexual behavior or drug use were not more likely to use condoms than were persons not at increased risk; only 22% used condoms during last intercourse within an ongoing relationship. CONCLUSIONS: Substantial progress has been made toward national goals for increasing condom use. The rates of condom use by individuals at high risk of HIV need to be increased, however, particularly condom use with a steady partner. (+info)Computed radiography dual energy subtraction: performance evaluation when detecting low-contrast lung nodules in an anthropomorphic phantom. (7/7400)
A dedicated chest computed radiography (CR) system has an option of energy subtraction (ES) acquisition. Two imaging plates, rather than one, are separated by a copper filter to give a high-energy and low-energy image. This study compares the diagnostic accuracy of conventional computed radiography to that of ES obtained with two radiographic techniques. One soft tissue only image was obtained at the conventional CR technique (s = 254) and the second was obtained at twice the radiation exposure (s = 131) to reduce noise. An anthropomorphic phantom with superimposed low-contrast lung nodules was imaged 53 times for each radiographic technique. Fifteen images had no nodules; 38 images had a total of 90 nodules placed on the phantom. Three chest radiologists read the three sets of images in a receiver operating characteristic (ROC) study. Significant differences in Az were only found between (1) the higher exposure energy subtracted images and the conventional dose energy subtracted images (P = .095, 90% confidence), and (2) the conventional CR and the energy subtracted image obtained at the same technique (P = .024, 98% confidence). As a result of this study, energy subtracted images cannot be substituted for conventional CR images when detecting low-contrast nodules, even when twice the exposure is used to obtain them. (+info)Cancer mortality in agricultural regions of Minnesota. (8/7400)
Because of its unique geology, Minnesota can be divided into four agricultural regions: south-central region one (corn, soybeans); west-central region two (wheat, corn, soybeans); northwest region three (wheat, sugar beets, potatoes); and northeast region four (forested and urban in character). Cancer mortality (1980-1989) in agricultural regions one, two, and three was compared to region four. Using data compiled by the National Center for Health Statistics, cancer mortality was summarized by 5-year age groups, sex, race, and county. Age-standardized mortality rate ratios were calculated for white males and females for all ages combined, and for children aged 0-14. Increased mortality rate ratios and 95% confidence intervals (CIs) were observed for the following cancer sites: region one--lip (men), standardized rate ratio (SRR) = 2.70 (CI, 1.08-6.71); nasopharynx (women), SRR = 3.35 (CI, 1.20-9.31); region two--non-Hodgkin's lymphoma (women), SRR = 1.35 (CI, 1.09-1.66); and region three--prostate (men), SRR = 1.12 (CI, 1.00-1.26); thyroid (men), SRR = 2.95 (CI, 1.35-6.44); bone (men), SRR = 2.09 (CI, 1. 00-4.34); eye (women), SRR = 5.77 (CI, 1.90-17.50). Deficits of smoking-related cancers were noted. Excess cancers reported are consistent with earlier reports of agriculturally related cancers in the midwestern United States. However, reports on thyroid and bone cancer in association with agricultural pesticides are few in number. The highest use of fungicides occurs in region three. Ethylenebisdithiocarbamates, whose metabolite is a known cause of thyroid cancer in rats, are frequently applied. This report provides a rationale for evaluation of the carcinogenic potential of this suspect agent in humans. (+info)
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AP Statistics Curriculum 2007 Chi-Square - Socr
Introduction to Probability and Statistics II | UNB
Contents - Applied Regression Modeling, 2nd edition
Biostatistik - HPM FK UGM
16.9.4 Confidence intervals when no events are observed
ASQ/ANSI/ISO 16269-7:2001: Statistical interpretation of data - Part 7: Median - Estimation and confidence intervals | ASQ
Week5&6 IntroInference - Week 5&6 Introduction to Inference Week 5&6 Introduction to Inference Confidence Intervals In...
For each set of sample outcomes below, use Formula 6.2 to construct the 95% confidence interval for estimating μ , the...
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Commute with Care and Confidence
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Mark and recapture
Confidence interval[edit]. An approximate 100. (. 1. −. α. ). %. {\displaystyle 100(1-\alpha )\%}. confidence interval for the ... It has been shown that this confidence interval has actual coverage probabilities that are close to the nominal 100. (. 1. −. α ... level even for small populations and extreme capture probabilities (near to 0 or 1), in which cases other confidence intervals ... Sadinle, Mauricio (2009-10-01). "Transformed Logit Confidence Intervals for Small Populations in Single Capture-Recapture ...
Rayleigh distribution
Confidence intervals[edit]. A (1 − α) confidence interval is given by N. x. 2. ¯. χ. α. /. 2. 2. ≤. σ. ^. 2. ≤. N. x. 2. ¯. χ. ... Given a random variate U drawn from the uniform distribution in the interval (0, 1), then the variate ...
Statistics
Confidence intervals: the red line is true value for the mean in this example, the blue lines are random confidence intervals ... Often they are expressed as 95% confidence intervals. Formally, a 95% confidence interval for a value is a range where, if the ... In principle confidence intervals can be symmetrical or asymmetrical. An interval can be asymmetrical because it works as lower ... left-sided interval or right sided interval), but it can also be asymmetrical because the two sided interval is built violating ...
Biostatistics
Confidence intervals. A confidence interval is a range of values that can contain the true real parameter value in given a ... Some of the best-known QTL mapping algorithms are Interval Mapping, Composite Interval Mapping, and Multiple Interval Mapping.[ ... The upper value of the interval is obtained by the sum of this estimate with the multiplication between the standard error of ... certain level of confidence. The first step is to estimate the best-unbiased estimate of the population parameter. ...
Allan variance
Confidence interval[edit]. The confidence interval can be established using chi-squared distribution by using the distribution ... Confidence intervals and equivalent degrees of freedom[edit]. Statistical estimators will calculate an estimated value on the ... Studying the effect on the confidence intervals that the length N of the sample series have, and the effect of the variable τ ... The confidence interval depends on the number of observations in the sample series, the dominant noise type, and the estimator ...
Stochastic programming
confidence interval for f. (. x. ). {\displaystyle f(x)}. : [. g. ^. N. (. x. ). −. z. α. /. 2. σ. ^. (. x. ). N. ,. g. ^. N. ( ...
Generalized additive model
which can be used to produce confidence/credible intervals for the smooth components, f. j. {\displaystyle f_{j}}. . The ... Nychka, D. (1988). "Bayesian confidence intervals for smoothing splines". Journal of the American Statistical Association. 83. ... Wahba, G. (1983). "Bayesian Confidence Intervals for the Cross Validated Smoothing Spline". Journal of the Royal Statistical ... Marra, G.; Wood, S.N. (2012). "Coverage properties of confidence intervals for generalized additive model components". ...
Evofosfamide
... confidence interval [CI]: 0.71 - 1.01; p=0.0589).[citation needed] Risks published in the quarterly/annual reports of Threshold ...
Permian-Triassic extinction event
Wang, S.C.; Everson, P.J. (2007). "Confidence intervals for pulsed mass extinction events". Paleobiology. 33 (2): 324-336. doi: ... percentage of marine genera that are present in each interval of time but do not exist in the following interval) vs time in ... Leighton, L.R.; Schneider, C.L. (2008). "Taxon characteristics that promote survivorship through the Permian-Triassic interval ... "Massive release of hydrogen sulfide to the surface ocean and atmosphere during intervals of oceanic anoxia". Geology. 33 (5): ...
Glycated hemoglobin
Data in parentheses are 95% confidence intervals. HbA1c. eAG %. mmol/mol[35]. mmol/L. mg/dL ...
Homo sapiens
95% confidence interval 237-581 kya)[60] *^ "Although none of the Qesem teeth shows a suite of Neanderthal characters, a few ...
Sorafenib
... confidence interval [CI], 0.35 to 0.55; P,0.01).[11] In Australia this is one of two TGA-labelled indications for sorafenib, ...
Muscle atrophy
... confidence interval of 0.11-0.594 kilograms (0.24-1.31 lb). The studies included in the meta-analysis had durations of 2-12 ... confidence interval: 0.11, 0.594; Z value=2.85; P=0.004). There were no significant fat mass changes between intervention and ... confidence interval: -0.32, 0.159; Z value=0.66; P=0.511). CONCLUSION: Beta-hydroxy-beta-methylbutyrate supplementation ...
Group size measures
Confidence interval for mean crowding.. Example[edit]. Imagine a sample with three groups, where group sizes are one, two, and ... Confidence interval for median group size.. Insiders' view of group size[edit]. As Jarman (1974) pointed out, average ... 2008) discuss the statistical problems associated with group size measures (calculating confidence intervals, two-sample tests ...
Sam Weerahandi
Lee, J. C., and Lin, S. H. (2004). Generalized confidence intervals for the ratio of means of two normal populations. Journal ... Mathew, T. and Webb, D. W. (2005). Generalized p-values and confidence intervals for variance components: Applications to Army ... Bebu, I., and Mathew, T. (2009). Confidence intervals for limited moments and truncated moments in normal and lognormal models ... Weerahandi, S. (1993). Generalized Confidence Intervals. JASA, 88, 899-905. Wu, J.F., and Hamada, M.S. (2009). Experiments: ...
Australians
See the source for 95 per cent confidence intervals. *^ "Australia's Rudd Dials Hong Kong Expats". The Wall Street Journal. 29 ...
Germans in the United Kingdom
See the source for 95 per cent confidence intervals. External links[edit]. *Goethe Institute London ...
Vietnamese people
See the source for 95 per cent confidence intervals. *^ "Vietnamese Community in Great Britain". Runnymede Trust. Retrieved ...
Islam in the United Kingdom
See the source for 95 per cent confidence intervals. *^ a b Dissanayake, Samanthi (4 December 2008). "British Somalis play ...
Bootstrapping (statistics)
... confidence interval will include the true variance only 78% of the time. The basic / reverse percentile confidence intervals ... then percentile confidence-intervals are often inappropriate. There are several methods for constructing confidence intervals ... If the bootstrap distribution of an estimator is symmetric, then percentile confidence-interval are often used; such intervals ... confidence-interval for the population median is (26, 28.5), which is close to the interval for (25.98, 28.46) for the smoothed ...
Bradley Efron
"Bootstrap confidence intervals for a class of parametric problems." Biometrika. Efron, B. (1987). "Better bootstrap confidence ... intervals". Journal of the American Statistical Association Efron, B. (1990). "More efficient bootstrap computations". Journal ...
Hormone replacement therapy
Nominal confidence intervals unadjusted for multiple looks and multiple comparisons. References[edit]. *^ a b c d e f g h i ... The relative risk of breast cancer also varies depending on the interval between menopause and HRT and route of administration. ...
Frequentist probability
Neyman's derivation of confidence intervals embraced the measure theoretic axioms of probability published by Kolmogorov a few ... Neyman formulated confidence intervals and contributed heavily to sampling theory; Neyman and Pearson paired in the creation of ... hypothesis testing and confidence intervals) all based on frequentist probability.. Alternatively,[11] Jacob Bernoulli (AKA ...
Statistical significance
"Conclusions about statistical significance are possible with the help of the confidence interval. If the confidence interval ... Confidence levels and confidence intervals were introduced by Neyman in 1937. Statistical significance plays a pivotal role in ... StatNews #73: Overlapping Confidence Intervals and Statistical Significance Neyman, J. (1937). "Outline of a Theory of ... ISBN 978-0-471-82211-0. Cumming, Geoff (2012). Understanding The New Statistics: Effect Sizes, Confidence Intervals, and Meta- ...
OpenMx
Confidence intervals are estimated robustly. The program has parallel processing built-in via links to parallel environments in ...
Federal Assault Weapons Ban
... confidence interval, 0.22-0.39). Smart, Rosanna (March 2, 2018). "Effects of Bans on the Sale of Assault Weapons and High- ...
Enzalutamide
... confidence interval, 0.15-0.23). In addition, a phase II trial began in March 2011 comparing enzalutamide with bicalutamide in ... confidence interval, range of 0.59-0.83), and radiographic progression-free survival, with an 81% reduction in risk of ...
Charles R. Marshall
Confidence intervals on stratigraphic ranges. Paleobiology 16:1-10. Presentation of the Charles Schuchert Award of the ... Marshall's first prominent work was on using confidence intervals to better estimate the full stratigraphic range of a lineage ...
Yup Technologies
Hypothesis testing and confidence intervals; Sampling and surveying; Other statistics Calculus Limits and continuity; ... continuity/interval notation); Inequalities (with variables); Absolute value (with variables); Systems of linear equations; ...
Human mortality from H5N1
... confidence interval, 1.06-1.23), and direct contact with sick poultry (odds ratio, 1.73; 95% confidence interval, 1.58-1.89). ... confidence interval, 0.96-1.12), sick or dead poultry in the household but with no direct contact (odds ratio, 1.14; 95% ... the mortality rates for the resulting human adapted pandemic strain cannot be predicted with any confidence. The global case ...
Level of measurement
Interval estimation. *Confidence interval. *Pivot. *Likelihood interval. *Prediction interval. *Tolerance interval. *Resampling ... Interval scale[edit]. The interval type allows for the degree of difference between items, but not the ratio between them. ... Thus, some argue that so long as the unknown interval difference between ordinal scale ranks is not too variable, interval ... distinction between nominal, ordinal, interval, and ratio numbers. Level of measurement or scale of measure is a classification ...
Neonatal conjunctivitis
According to them the incidence of Neonatal conjunctivitis (Ophthalmia Neonatorum) in England was 257 (95% confidence interval ...
Mann-Whitney U test
Nakagawa, Shinichi; Cuthill, Innes C (2007). "Effect size, confidence interval and statistical significance: a practical guide ... A non-parametric 0.95 confidence interval for HLΔ accompanies these estimates as does ρ, an estimate of the probability that a ... The Mann-Whitney U test is preferable to the t-test when the data are ordinal but not interval scaled, in which case the ... so one can recommend the Mann-Whitney U test as the default test for comparing interval or ordinal measurements with similar ...
Yellow fever
... confidence interval 1701 to 1911).[49] The historical record shows an outbreak of yellow fever occurred in Recife, Brazil, ...
Tetrapod
"Assessing confidence intervals for stratigraphic ranges of higher taxa: the case of Lissamphibia" (PDF). Acta Palaeontologica ...
Homo habilis
At 61-76 cm (2-2.5 ft) intervals, rocks were piled up to 15-23 cm (6-9 in) high. Mary Leakey suggested the rock piles were used ... However, it is highly difficult to speculate with any confidence the group dynamics of early hominins. The degree of sexual ...
Fluvoksamin bahasa Indonesia, ensiklopedia bebas
53% (90% confidence interval: 44-62%)[2] Ikatan protein 77-80%[2][3] ...
Lobbying
An example of such a figure was Sir John Hay, who spent frequent intervals at court during [the reigns of James VI/I and ...
Forensic entomology
This can be helpful in determining a post mortem interval (PMI) and location of a death in question. Since many insects exhibit ... to the measured values of gene expression to accurately predict the age of an egg to within two hours with a high confidence ... The post-decay time interval, beginning at day six after death and ending around day 15 after death, is greatly reduced from ... Contemporary precision, bias and accuracy of minimum post-mortem intervals estimated using development of carrion-feeding ...
Isotonic regression
Interval estimation. *Confidence interval. *Pivot. *Likelihood interval. *Prediction interval. *Tolerance interval. *Resampling ...
James Clerk Maxwell
Certainly, his knowledge of the Bible was remarkable, so his confidence in the Scriptures was not based on ignorance. ... From 1855 to 1872, Maxwell published at intervals a series of investigations concerning the perception of colour, colour- ...
Age of the universe
68% limits: Parameter 68% confidence limits for the base ΛCDM model TT, TE, EE: Planck Cosmic microwave background (CMB) power ... the precision of the meaning would be lost because the minuscule latter time interval is eclipsed by uncertainty in the former ...
Probability distribution
Interval estimation. *Confidence interval. *Pivot. *Likelihood interval. *Prediction interval. *Tolerance interval. *Resampling ... As notated on the figure, the probabilities of intervals of values correspond to the area under the curve. ... that the outcome lies in a given interval can be computed by integrating the probability density function over that interval. ... such as intervals, can have positive probability. For example, the probability that a given object weighs exactly 500 g is zero ...
Chronology of the universe
The Planck Collaboration in 2015 published the estimate of 13.799 ± 0.021 billion years ago (68% confidence interval). See ... lowered confidence in confirming the cosmic inflation findings was reported [9][11][12] and finally, on February 2, 2015, a ... "Cosmic inflation: Confidence lowered for Big Bang signal". BBC News. Retrieved June 20, 2014 ...
Influenza
The regression model attributes an annual average of 41,400 (95% confidence interval: 27,100, 55,700) deaths to influenza over ... "Long intervals of stasis punctuated by bursts of positive selection in the seasonal evolution of influenza A virus". Biology ...
Probiotic
control groups, 95% confidence interval, 16-34 hours), also noting, however, that "the differences between the studies may be ...
Opinion poll
If the statistic is a percentage, this maximum margin of error can be calculated as the radius of the confidence interval for a ... The margin of error is usually defined as the radius of a confidence interval for a particular statistic from a survey. One ... confidence interval of the sample estimate plus or minus 3%. The margin of error can be reduced by using a larger sample, ... of a population by conducting a series of questions and then extrapolating generalities in ratio or within confidence intervals ...
Chi-squared test
Interval estimation. *Confidence interval. *Pivot. *Likelihood interval. *Prediction interval. *Tolerance interval. *Resampling ...
Random assignment
Interval estimation. *Confidence interval. *Pivot. *Likelihood interval. *Prediction interval. *Tolerance interval. *Resampling ...
Mexican Revolution
... confidence in Madero's presidency, brokered the Pact of the Embassy, which formalized the alliance between Félix Díaz and ... with rigged elections held at regular intervals to give the appearance of democracy. ...
Jeju Island
Results show that of the 55 confirmed cases of SFTS, the case fatality rate was 10.9% (95% confidence interval [CI], 4.1 to ...
Student's t-test
Interval estimation. *Confidence interval. *Pivot. *Likelihood interval. *Prediction interval. *Tolerance interval. *Resampling ...
Gugur kandungan bahasa Indonesia, ensiklopedia bebas
... it was not possible to compute confidence intervals based on standard errors around the estimates. Drawing on the information ... We computed wider intervals for unsafe abortion rates than for safe abortion rates. The basis for these intervals included ... we computed intervals of certainty around these rates (webappendix). ...
Level of measurement
Interval estimation. *Confidence interval. *Pivot. *Likelihood interval. *Prediction interval. *Tolerance interval. *Resampling ... Interval scale[edit]. The interval type allows for the degree of difference between items, but not the ratio between them. ... Thus, some argue that so long as the unknown interval difference between ordinal scale ranks is not too variable, interval ... Interval Difference, affinity +, − Yardstick Arithmetic mean Deviation Ratio Magnitude, amount ×, / Ratio Geometric mean, ...
Cretaceous-Paleogene extinction event
MacLeod, N (1996). "Nature of the Cretaceous-Tertiary (K-T) planktonic foraminiferal record: Stratigraphic confidence intervals ... Earth and Life: Global Biodiversity, Extinction Intervals and Biogeographic Perturbations Through Time. Springer. pp. 759-793. ... Current research cannot ascertain, however, whether the extinctions occurred prior to, or during, the boundary interval.[43][44 ... of marine animal genera becoming extinct during any given time interval. It does not represent all marine species, just those ...
Australians
See the source for 95 per cent confidence intervals. *^ "Australia's Rudd Dials Hong Kong Expats". The Wall Street Journal. 29 ...
Structural equation modeling
Interval estimation. *Confidence interval. *Pivot. *Likelihood interval. *Prediction interval. *Tolerance interval. *Resampling ...
Tajima's D
value for a sample of sequences is outside the confidence interval then one can reject the null hypothesis of neutral mutation ... These authors advocated constructing a confidence interval for the true theta value, and then performing a grid search over ... this interval to obtain the critical values at which the statistic is significant below a particular alpha value. An ...
Confidence interval - Wikipedia
Confidence interval for specific distributions[edit]. *Confidence interval for binomial distribution. *Confidence interval for ... A confidence interval for the parameter θ, with confidence level or confidence coefficient γ, is an interval with random ... Confidence region[edit]. Main article: Confidence region. Confidence regions generalize the confidence interval concept to deal ... An interactive introduction to Confidence Intervals. *Confidence Intervals: Confidence Level, Sample Size, and Margin of Error ...
Calculating confidence intervals
... such interval estimates called confidence intervals Joe calculates the general formula for all confidence intervals is equal to ... An interval estimate provides more information about a population characteristic than does a point estimate and therefore ... provides a confidence level for the estimate. Joe Schmuller investigates ... such interval estimates called confidence intervals Joe calculates the general formula for all confidence intervals is equal to ...
Statistical significance and confidence intervals | The BMJ
Confidence intervals for probability distribution parameters - MATLAB paramci
... confidence interval for each parameter in probability distribution pd. ... Confidence interval. array. Confidence interval, returned as a p-by-2 array containing the lower and upper bounds of the 100(1- ... to compute the confidence intervals using the Wald method, or lr. to compute the confidence intervals using the likelihood ... For example, you can specify a different percentage for the confidence interval, or compute confidence intervals only for ...
Robust misinterpretation of confidence intervals | SpringerLink
Confidence intervals make a difference: Effects of showing confidence intervals on inferential reasoning. Educational and ... Jaynes, E. T. (1976). Confidence intervals vs Bayesian intervals. In W. L. Harper & C. A. Hooker (Eds.), Foundations of ... Confidence intervals (CIs) have frequently been proposed as a more useful alternative to NHST, and their use is strongly ... Cumming, G., & Finch, S. (2001). A primer on the understanding, use, and calculation of confidence intervals that are based on ...
Confidence intervals for partially identified parameters
... the identification region is an interval whose lower and upper bounds may be estimated from sample data. Confidence intervals ... and in large samples is comparable to the difference of one and twosided confidence intervals. A complication arises from the ... Here we introduce conceptually different interval estimates that asymptotically cover each element in the identification region ... Horowitz and Manski (1998, 2000) proposed and applied interval estimates that asymptotically cover the entire identification ...
Confidence Intervals for Partially Identified Parameters
For this case confidence intervals (CIs) have been proposed that cover the entire identification region with fixed probability ... Here, we introduce a conceptually different type of confidence interval. Rather than cover the entire identification region ... In many cases the parameter is real-valued and the identification region is an interval whose lower and upper bounds may be ... "Confidence intervals for partially identified parameters," CeMMAP working papers CWP09/03, Centre for Microdata Methods and ...
Confidence intervals for the number needed to treat | The BMJ
Confidence intervals for the number needed to treat BMJ 1998; 317 :1309 ... Reanalyzing a Randomized Controlled Trial of Combination Antidepressant Treatment With Mirtazapine: Confidence Intervals ... Missing the point (estimate)? Confidence intervals for the number needed to treat ... Confidence intervals for the number needed to treat. BMJ 1998; 317 doi: https://doi.org/10.1136/bmj.317.7168.1309 (Published 07 ...
st: standardized confidence intervals using mlogit
... From. Staimez, Lisa Rachel ,[email protected],. To. [email protected] ... st: standardized confidence intervals using mlogit. Date. Mon, 19 Sep 2011 19:38:43 +0000. Dear Listers, I have been trying ... Can someone please point me to the right command or tell me how to produce the confidence intervals? Second, I am unable to ... RE: st: standardized confidence intervals using mlogit *From: Cameron McIntosh ,[email protected], ...
Re: [R-sig-phylo] Confidence intervals for B in ape::binaryPGLMM
... Emmanuel Paradis Fri, 22 Sep 2017 02:56:33 -0700 ... However, can I calculate confidence intervals for the regression coefficients? One way to get some numbers is to define the ... R-sig-phylo] Confidence intervals for B in ape::binar... Wouter van der Bijl ... Re: [R-sig-phylo] Confidence intervals for B ... Wouter van der Bijl ...
RE: st: standardized confidence intervals using mlogit
... From. Cameron McIntosh ,[email protected],. To. STATA LIST ,[email protected] ... RE: st: standardized confidence intervals using mlogit. Date. Mon, 19 Sep 2011 17:02:09 -0400. Lisa, Im not sure, but I think ... Can someone please point me to the right command or tell me how to produce the confidence intervals? , , Second, I am unable to ... st: standardized confidence intervals using mlogit *From: Staimez, Lisa Rachel ,[email protected], ...
Bootstrapping - Confidence Intervals, Bootstrapping, and Plotting | Coursera
This module covers Confidence Intervals, Bootstrapping, and Plotting. These are core concepts in mathematical biostatistics and ... These percentile confidence intervals. Theyre not very good.. You can improve on bootstrap confidence intervals by correcting ... Confidence Intervals, Bootstrapping, and Plotting. This module covers Confidence Intervals, Bootstrapping, and Plotting. These ... the intervals. And the bootstrap procedure, the one I. would recommend is this so called BCA, confidence interval, the ...
Confidence Intervals for Proportions and Related Measures of Effect Si
... and Related Measures of Effect Size illustrates the use of effect size measures and corresponding confidence intervals as m ... Hypothesis Tests and Confidence Intervals. Means and Their Differences. Confidence Intervals for a Simple Binomial Proportion. ... Evaluation of Performance of Confidence Interval Methods. Intervals for the Poisson Parameter and the Substitution Approach. ... Confidence Intervals for Proportions and Related Measures of Effect Size By Robert Gordon Newcombe. ...
Statistical Methods: Confidence Intervals | U.S. Cancer Statistics Data Visualizations Tool Technical Notes | CDC
Explains how confidence intervals are calculated in United States Cancer Statistics. ... Confidence intervals reflect the range of variation in the estimation of the cancer rates. The width of a confidence interval ... Modified Gamma Intervals. Confidence intervals that are expected to include the true underlying rate 95% of the time are used ... Confidence intervals for directly standardized rates: a method based on the gamma distribution.external icon Statistics in ...
Confidence intervals | Statistics and probability | Math | Khan Academy
This topic covers confidence intervals for means and proportions. ... Confidence intervals give us a range of plausible values for ... Confidence intervals give us a range of plausible values for some unknown value based on results from a sample. This topic ... Sample size and margin of error in a confidence interval for a meanGet 3 of 4 questions to level up! ... Conditions for confidence interval for a proportion worked examples. (Opens a modal) ...
Jones et al [1998]: Confidence Intervals « Climate Audit
... which purports to provide confidence intervals for the J98 reconstruction (blue). Theres (at least) one really strange feature ... If this is not the case then the confidence interval of average annual temperature IMHO is as big as 1 Kelvin, being the ... Jones et al [1998]: Confidence Intervals. Im working away at Jones et al [1998]. Heres an interesting diagram from Jones et ... If you have spurious regression, you have spurious confidence intervals. In the case of MBH, as far as I can tell, they ...
Confidence Intervals for fMRI Activation Maps
Neuroimaging activation maps typically color voxels to indicate whether the blood oxygen level-dependent (BOLD) signals measured among two or more experimental conditions differ significantly at that location. This data presentation, however, omits information critical for interpretation of experimental results. First, no information is represented about trends at voxels that do not pass the statistical test. Second, no information is given about the range of probable effect sizes at voxels that do pass the statistical test. This leads to a fundamental error in interpreting activation maps by naïve viewers, where it is assumed that colored,
Confidence Intervals for Probabilities of Default by Samuel Gregory Hanson, Til Schuermann :: SSRN
In this paper we conduct a systematic comparison of confidence intervals around estimated probabilities of default (PD) using ... Confidence Intervals for Probabilities of Default. Number of pages: 44 Posted: 05 Aug 2005 ... We show how the large differences between the point estimates and confidence intervals of these two estimators are consistent ... In this paper we conduct a systematic comparison of confidence intervals around estimated probabilities of default (PD) using ...
Confidence Interval for a Population Mean
A) The 90% confidence interval for B) The 95% confidence interval for C) The 99% confidence interval for (1) Given. = 5.98. = ... is called the confidence coefficient or confidence level and the interval, , is called the confidence interval for .. Note that ... 99% confidence interval (The correct value of t for a 99% confidence interval with 9 degrees of freedom is 3.2498). 119 3.2498 ... An approximate confidence interval for is given by:. Components of an interval estimate. This is the general form for an ...
Confidence Intervals.
Confidence intervals
... im not asking to do the problems because i really want to learn this. i just need a little help ... 1) A random sample size of 4 has a sample mean of 75 and a sample standard deviation of 8. Find the 99% confidence interval of ... interval of the population mean.. 4) You take a random sample of 36 from a population of mean 48 and SD of 12. find the ... You wish to estimate the population mean with a margin of error of 10 at the 95% confidence level. What is the minimum sample ...
Compute confidence intervals for model predictions (requires Statistics and Machine Learning Toolbox) - MATLAB sbiopredictionci
... confidence intervals for the model simulation results from fitResults, an NLINResults object or OptimResults object returned by ... Confidence interval type. gaussian. (default) , bootstrap. Confidence interval type, specified as the comma-separated pair ... Plot Confidence Intervals for Model Predictions. The confidence interval for each group is plotted in a separate column, and ... Logical flag to compute confidence intervals in parallel. true. , false. Logical flag to compute confidence intervals in ...
Inference by eye: confidence intervals and how to read pictures of data. - PubMed - NCBI
Inference by eye: confidence intervals and how to read pictures of data.. Cumming G1, Finch S. ... Wider use in psychology of confidence intervals (CIs), especially as error bars in figures, is a desirable development. However ... Wider use of interval estimation in psychology has the potential to improve research communication substantially. ... and interpret the intervals. They also include guidelines for inferential interpretation of the overlap of CIs on independent ...
Publication Bias in Meta-Analysis: Confidence Intervals for Rosenthal's Fail-Safe Number
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Robust confidence intervals - Wikipedia
In statistics a robust confidence interval is a robust modification of confidence intervals, meaning that one modifies the non- ... Before trusting the results of 100 objects weighed just three times each to have confidence intervals calculated from σ, it is ... The 200 extra weighings served only to detect and correct for operator error and did nothing to improve the confidence interval ... A bootstrap calculation could be used to determine a confidence interval narrower than that calculated from σ, and so obtain ...
Profile Likelihood Confidence Intervals :: SAS/ETS(R) 12.1 User's Guide
The endpoints of a confidence interval are the zeros of the function . Computing a likelihood-ratio-based confidence interval ... Wald-based and likelihood-ratio-based confidence intervals are available in the MODEL procedure for computing a confidence ... By default, the PRL option produces 95% likelihood ratio confidence limits. The coverage of the confidence interval is ... interval on an estimated parameter. A confidence interval on a parameter can be constructed by inverting a Wald-based or a ...
Confidence Interval Example - Measures of Association | Coursera
This module introduces measures of association and confidence intervals. Learn online and earn valuable ... ... Confidence Interval Example. To view this video please enable JavaScript, and consider upgrading to a web browser that supports ... This module introduces measures of association and confidence intervals.. Confidence Intervals9:11 ...
Bootstrap confidence intervals for industrial recurrent event data
4 CONFIDENCE INTERVALS FOR MCF In this Section, the usual procedure to calculate confidence limits for the Mean Cumulative ... 4.1 Confidence Intervals Based on Asymptotic Theory. Suppose that N cumulative history functions for cost represented in Figure ... 4.2 Confidence Intervals Based on the Bootstrap. The bootstrap is a computer-intensive method which can be used to obtain ... On the number of bootstrap simulations required to construct a confidence interval. The Annals of Statistics, 14: 125-129. ...
WikiGenes - Confidence Intervals
... confidence interval = 1.03-100) [38].. *RESULTS: Three (12%, exact 95% confidence interval [CI] = 2% to 30%) families carried ... 95 percent confidence interval, 1.5 to 7.6) [18].. *The 95 percent confidence intervals for the difference between the controls ... 95 percent confidence interval, 37 to 78 percent) and 94 percent (95 percent confidence interval, 86 to 100 percent), ... 95 percent confidence interval, 28 to 71) in the amphotericin B group and 64 days (95 percent confidence interval, 53 to 67) in ...
EstimatesEstimationParametersParameterStatisticalStandard deviationProportionEstimatorsSimple linear regInferenceHypothesisCalculatingLogistic regressionProportionsInterpretationAsymptotic confidence intervalsProbabilities of DefaultSignificanceCalculate confidenceNarrowerCalculatesUpper boundFormulasStatisticsDirectly standardized ratesInterpret confidence intervalsLikelihood-based confidence intervalsEstimatorCompute the 95DistributionsOdds ratioApproximate 95ProcedureDegrees of freeResulting intervals are usuallyMethods1.96Construct a confidence intervalLevelAnovaLinear RegressionDataLessonSampleDependsCalculation of a confidence intervalBayesConceptually differentExamplesEmpiricalBootstrap methodPrediction intervalsFind a confidence intervalCommonly
Estimates24
- Confidence intervals are commonly reported in tables or graphs along with point estimates of the same parameters, to show the reliability of the estimates. (wikipedia.org)
- Joe Schmuller investigates such interval estimates called confidence intervals Joe calculates the general formula for all confidence intervals is equal to Point Estimate ± (Critical Value)(Standard Error) by scaffolding the steps towards determinig critical value and standard error. (lynda.com)
- The intervals next to the parameter estimates are the 95% confidence intervals for the distribution parameters. (mathworks.com)
- Confidence intervals may be constructed to take account of the sampling variation in estimates of these bounds. (repec.org)
- Horowitz and Manski (1998, 2000) proposed and applied interval estimates that asymptotically cover the entire identification region with fixed probability. (repec.org)
- Here we introduce conceptually different interval estimates that asymptotically cover each element in the identification region with fixed probability (but not necessarily every element simultaneously). (repec.org)
- Furthermore when I use the std command alone I can't see the confidence intervals the standardized estimates. (stata.com)
- We find that the bootstrapped intervals for the duration based estimates are relatively tight when compared to either analytic or bootstrapped intervals around the less efficient cohort estimator. (ssrn.com)
- We show how the large differences between the point estimates and confidence intervals of these two estimators are consistent with non-Markovian migration behavior. (ssrn.com)
- Interval estimates are based on sampling distributions. (kean.edu)
- There are two ways in which interval estimates can be interpreted. (kean.edu)
- In this paper, we propose a technique based on the bootstrap method to have interval estimates for the cost and the number of cumulative events. (scielo.br)
- This paper presents the methodology for obtaining confidence interval estimates of these indices utilizing routinely available output from multiple logistic regression software. (nih.gov)
- My remarks are confined to settings in which P -values and confidence intervals accompany estimates of effect measures, such as the relative risk. (lww.com)
- LOD support intervals are the most commonly used interval estimates for the location of a QTL. (genetics.org)
- The parts of mean square error (MSEs) and credible intervals lengths, the estimators of Bayes depend on non-informative implement more effective than the maximum likelihood estimates (MLEs) and bootstrap. (scirp.org)
- The maximum likelihood estimates of the parameters of the WG distribution, the point and interval estimates of the parameters, as well as the approximate joint confidence region are studied in Section 4. (scirp.org)
- An interesting feature of the plot is that Random Forests doesn't appear to have the same confidence in all of its estimates, sometimes being less confident about estimates closer to the diagonal than those further away. (r-bloggers.com)
- Students will calculate point estimates, find mimimum sample sizes needed to estimate the population parameters, and construct confidence intervals. (teacherspayteachers.com)
- There are two types of estimates for each population parameter: the point estimate and confidence interval (CI) estimate. (bu.edu)
- Confidence intervals for the between study variance are useful in random-effects meta-analyses because they quantify the uncertainty in the corresponding point estimates. (biomedcentral.com)
- When the design and size of the study has been decided it may be useful to know which results in terms of the parameter estimates that will produce a statistical significance or a given width of a confidence interval. (studyresult.com)
- If we were to repeatedly make new estimates using exactly the same procedure (by drawing a new sample, conducting new interviews, calculating new estimates and new confidence intervals), the confidence intervals would contain the average of all the estimates 90% of the time. (stlouisfed.org)
- Using bootstrap methods, properties of various trimmed elemental estimator interval estimates to allow for inference are examined and estimates with ordinary least squares (OLS) and least sum of absolute values (LAV) are compared. (wayne.edu)
Estimation18
- Interval estimation can be contrasted with point estimation . (wikipedia.org)
- A major factor determining the length of a confidence interval is the size of the sample used in the estimation procedure, for example, the number of people taking part in a survey. (wikipedia.org)
- Confidence intervals reflect the range of variation in the estimation of the cancer rates. (cdc.gov)
- Efficient interval estimation for age-adjusted cancer rates. (cdc.gov)
- For details about the meaning of each estimation status, see Parameter Confidence Interval Estimation Status . (mathworks.com)
- Wider use of interval estimation in psychology has the potential to improve research communication substantially. (nih.gov)
- Herein, we look at the possibilities to construct confidence intervals for sample averages when only ranges are available with maximum likelihood estimation with order statistics (MLEOS). (mdpi.com)
- The purpose of this article offers different algorithms of Weibull Geometric (WG) distribution estimation depending on the progressive Type II censoring samples plan, spatially the joint confidence intervals for the parameters. (scirp.org)
- But since we do not know the true value it's a bit like Schrödinger's cat… To keep things very sketchy: The width of the interval gives you an indication of your estimation certainty, but the particular values are hard to interpret - except maybe as the critical limits in a corresponding hypothesis test. (r-bloggers.com)
- Here, we present a mathematically rigorous approach that integrates peptide signal strengths and peptide-measurement agreement into an estimation of the true protein ratio and the associated confidence (BACIQ). (mcponline.org)
- In statistics, interval estimation is the use of sample data to calculate an interval of possible values of an unknown population parameter, in contrast to point estimation, which is a single number. (absoluteastronomy.com)
- Neyman identified interval estimation as distinct from point estimation. (absoluteastronomy.com)
- In Bayesian statistics, a credible interval is an interval in the domain of a posterior probability distribution used for interval estimation. (absoluteastronomy.com)
- Explicit Formulas for Confidence Interval Estimation in Discrete Distributions* (McCulloch, Charles E. (cornell.edu)
- paper is important in putting all these various ideas together and making it clear what are the unstated assumptions of interval estimation. (andrewgelman.com)
- Confidence intervals are the most prevalent form of interval estimation. (powerofcharismabook.com)
- Hi, I have the following problem: I want to draw confidence band for a quadratic regression I have the model: y=a+b*x+c*x^2, i have estimation for a,b and c together with their standard error. (talkstats.com)
- Confidence statistics is an estimation method used to predict if a subsequent sampling of data will fall within a given interval given a level of confidence. (electronicsproductionworld.com)
Parameters20
- For example, you can specify a different percentage for the confidence interval, or compute confidence intervals only for selected parameters. (mathworks.com)
- Compute the 99% confidence interval for the distribution parameters. (mathworks.com)
- Confidence intervals for partially identified parameters ," CeMMAP working papers CWP09/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies. (repec.org)
- interval for parameters, based on kind of difficult to work with statistics. (coursera.org)
- To request confidence intervals on estimated parameters, specify the PRL= option in the FIT statement. (sas.com)
- Using Monte Carlo simulations, we examine coverage and interval width for location parameters estimated form ranges. (mdpi.com)
- The approximate joint confidence intervals for the parameters, the approximate confidence regions and percentile bootstrap intervals of confidence are discussed, and several Markov chain Monte Carlo (MCMC) techniques are also presented. (scirp.org)
- Comparing the models, the MSEs, average confidence interval lengths of the MLEs, and Bayes estimators for parameters are less significant for censored models. (scirp.org)
- 18] studied the confidence intervals for parameters of inverse Weibull distribution based on MLE and bootstrap. (scirp.org)
- The parametric bootstrap confidence intervals of parameters are discussed in Section 5. (scirp.org)
- 2 where ¸(y) and º (y) are the lower and upper confidence limits, respectively, for the observed y, ½ is the random variable associated with y, is the parameter of interest, and is a vector of nuisance parameters. (cdc.gov)
- A method is derived to efficiently compute nonlinear confidence and prediction intervals on any function of parameters derived as output from a mathematical model of a physical system. (usgs.gov)
- To obtain confidence and prediction intervals resulting from uncertainties in parameters, the calibrated model and information on extreme ranges and ordering of the model parameters within one or more independent groups are required. (usgs.gov)
- If random errors in the dependent variable are present in addition to uncertainties in parameters, then calculation of prediction intervals also requires information on the extreme range of error expected. (usgs.gov)
- Application of the method to a hypothetical example showed that inclusion of random errors in the dependent variable in addition to uncertainties in parameters can considerably widen the prediction intervals. (usgs.gov)
- The third case uses nonparametric methods to find the confidence interval for mu, meaning we use inferential methods that are not concerned with parameters- such as the population mean or population standard deviation. (study.com)
- The implications of positive and negative correltion on the confidence intervals of the parameters. (bionicturtle.com)
- The confidence interval depends on a variety of parameters, like the number of people taking the survey and the way they represent the whole group. (explorable.com)
- StudyResult is a program for quick calculation of p-values and confidence intervals for the most common tests and parameters. (studyresult.com)
- Confidence intervals and coverage probabilities for the estimators using a variety of error distributions, sample sizes, and number of parameters are examined. (wayne.edu)
Parameter44
- In statistics , a confidence interval ( CI ) is a type of interval estimate , computed from the statistics of the observed data, that might contain the true value of an unknown population parameter . (wikipedia.org)
- The interval has an associated confidence level that, loosely speaking, quantifies the level of confidence that the parameter lies in the interval. (wikipedia.org)
- More strictly speaking, the confidence level represents the frequency (i.e. the proportion) of possible confidence intervals that contain the true value of the unknown population parameter. (wikipedia.org)
- In other words, if confidence intervals are constructed using a given confidence level from an infinite number of independent sample statistics, the proportion of those intervals that contain the true value of the parameter will be equal to the confidence level. (wikipedia.org)
- Confidence intervals consist of a range of potential values of the unknown population parameter . (wikipedia.org)
- However, the interval computed from a particular sample does not necessarily include the true value of the parameter. (wikipedia.org)
- An interval estimate specifies instead a range within which the parameter is estimated to lie. (wikipedia.org)
- There is a 90% probability that the calculated confidence interval from some future experiment encompasses the true value of the population parameter. (wikipedia.org)
- Note this is a probability statement about the confidence interval, not the population parameter. (wikipedia.org)
- contains the lower and upper 95% confidence interval boundaries for the mu parameter, and column 2 contains the boundaries for the sigma parameter. (mathworks.com)
- In many cases where the parameter of interest is realvalued, the identification region is an interval whose lower and upper bounds may be estimated from sample data. (repec.org)
- A complication arises from the fact that the simplest version of the proposed interval is discontinuous in the limit case of point identification, leading to coverage rates that are not uniform in important subsets of the parameter space. (repec.org)
- Intervals for the Poisson Parameter and the Substitution Approach. (routledge.com)
- Compute 95% confidence intervals for each estimated parameter in the unpooled fit. (mathworks.com)
- Wald-based and likelihood-ratio-based confidence intervals are available in the MODEL procedure for computing a confidence interval on an estimated parameter. (sas.com)
- Here we will highlight how one technique, the confidence interval , can be used to estimate a parameter from a subsample dataset . (visionlearning.com)
- Under this formulation, the confidence interval represents those values of the population parameter that would have large p-values if they were tested as a hypothesized population proportion. (wikipedia.org)
- It is an observed interval (i.e. it is calculated from the observations), in principle different from sample to sample, that frequently includes the parameter of interest, if the experiment is repeated. (absoluteastronomy.com)
- How frequently the observed interval contains the parameter is determined by the confidence level or confidence coefficient . (absoluteastronomy.com)
- A confidence interval with a particular confidence level is intended to give the assurance that, if the statistical model is correct, then taken over all the data that might have been obtained, the procedure for constructing the interval would deliver a confidence interval that included the true value of the parameter the proportion of the time set by the confidence level. (absoluteastronomy.com)
- A confidence interval does not predict that the true value of the parameter has a particular probability of being in the confidence interval given the data actually obtained. (absoluteastronomy.com)
- A confidence interval is an interval whose endpoints are statistics (numbers calculated from a random sample) whose purpose is to estimate a parameter (a number that could, in theory, be calculated from the population, if measurements were available for the whole population). (umn.edu)
- The confidence level of a confidence interval is the probability (conventionally expressed as a percent, though this is archaic) that the confidence interval actually contains the parameter. (umn.edu)
- CONFIDENCE INTERVAL refers to a range of values defined such that there is a specified probability that the value of a true population parameter lies within that range. (assignmenthelp.net)
- A confidence interval is a range of values that expresses the uncertainty associated with a parameter, like the population mean. (study.com)
- The confidence interval does not reflect the variability in the unknown parameter. (bu.edu)
- Another way of thinking about a confidence interval is that it is the range of likely values of the parameter (defined as the point estimate + margin of error) with a specified level of confidence (which is similar to a probability). (bu.edu)
- The calculation of a confidence interval, which together with the hypothesis testing is the best known procedure of inferential statistics, has as result the probability that a certain statistical parameter is contained in a certain part of the real line. (aracneeditrice.it)
- This treatment of the confidence interval is then specified for the two cases, of great importance in the experimental sciences, when the statistical parameter is the mean or variance of a normal random variable. (aracneeditrice.it)
- and the confidence coefficient of the interval (typically 95%) is thought to index the plausibility that the true parameter is included in the interval. (andrewgelman.com)
- A confidence interval for an unknown parameter consists of an interval of values. (slideserve.com)
- The level of confidence represents the expected proportion of intervals that will contain the parameter if a large number of different samples is obtained. (slideserve.com)
- 0.05) implies that if 100 different confidence intervals are constructed, each based on a different sample from the same population, we will expect 95 of the intervals to contain the parameter and 5 to not include the parameter. (slideserve.com)
- The margin of error of a confidence interval estimate of a parameter is a measure of how accurate the point estimate is. (slideserve.com)
- A range of values which will capture the value of the parameter of interest with some level of confidence. (coursehero.com)
- 2 / 46 Week 5&6: Introduction to Inference Confidence Intervals A confidence interval gives possible values for a parameter, not a statistic. (coursehero.com)
- 3 / 46 Week 5&6: Introduction to Inference Confidence Intervals If a value is not covered by a confidence interval (it is not included in the range), then it is not a plausible value for the parameter in question and should be rejected as a plausible value for the population parameter. (coursehero.com)
- In general, a confidence interval is centered on our best guess for the parameter, the appropriate statistic. (coursehero.com)
- I guess that one of them computes the simplified Wald interval, (and the most common) of dividing the parameter estimate with its standard error. (talkstats.com)
- We also show some further results for a real example that illustrates how shorter confidence intervals for the between-study variance can be useful when performing sensitivity analyses for the average effect, which is usually the parameter of primary interest. (biomedcentral.com)
- A confidence interval is a range of values that is likely to contain an unknown population parameter. (electronicsproductionworld.com)
- In statistics a confidence interval is a special form of estimating a certain parameter. (electronicsproductionworld.com)
- With this method, a whole interval of acceptable values for the parameter is given instead of a single value, together with a likelihood that the real (unknown) value of the parameter will be in the interval. (electronicsproductionworld.com)
- Statisticians use a confidence interval to describe the amount of uncertainty associated with a sample estimate of a population parameter. (electronicsproductionworld.com)
Statistical7
- We provide an interpretation for the confidence interval for a binomial proportion hidden as the transcript of an hypothetical statistical consulting session. (r-bloggers.com)
- Our analysis differs from the previous literature by explicating and developing confidence intervals which provide measures of statistical reliability for the estimators and thus enhance the results of prior research. (defaultrisk.com)
- Regarding the general issue that confidence intervals are no inferential panacea, see my recent article , "P values and statistical practice," in which I discuss the problem of taking a confidence interval from a flat prior and using it to make inferences and decisions. (andrewgelman.com)
- Embodiments of the invention may likewise be used in alternative statistical applications, including computation of confidence intervals and likelihood ratios. (google.com)
- In statistics, confidence interval refers to the amount of error that is allowed in the statistical data and analysis. (explorable.com)
- In normal statistical analysis, the confidence interval tells us the reliability of the sample mean as compared to the whole mean. (explorable.com)
- Hence for other methods we would have to further explore if shorter confidence intervals were due to lower coverage probabilities rather than using better statistical methods. (biomedcentral.com)
Standard deviation8
- If we're given a sample mean, sample standard deviation,…sample size, and alpha,…what we can do is use the sampling distribution of the mean…to find the one minus alpha confidence interval. (lynda.com)
- Before trusting the results of 100 objects weighed just three times each to have confidence intervals calculated from σ, it is necessary to test for and remove a reasonable number of outliers (testing the assumption that the operator is careful and correcting for the fact that he is not perfect), and to test the assumption that the data really have a normal distribution with standard deviation σ. (wikipedia.org)
- In this lesson, you're going to learn how to construct a confidence interval when the population's standard deviation is known and the population is normally distributed. (study.com)
- But for this lesson we are going to pretend that the population standard deviation denoted by the symbol sigma, is known to us and we are going to use that to help us construct the confidence interval for the population mean , which itself is denoted by the symbol mu. (study.com)
- S ps t followed by MAD t are recommended at any rate of contamination, while Student t is not preferred at all for contaminated data and the sample mean and the sample standard deviation are not good choices for constructing confidence interval, but highly recommended for normal data without outliers as expected. (scialert.net)
- Instructions: Use this Confidence Interval Calculator for the population mean \(\mu\), in the case that the population standard deviation \(\sigma\) is not known, and we. (mathcracker.com)
- Standard deviation of the population: The more spread there is in the population, the wider our interval will be for a given level of confidence. (slideserve.com)
- Correspondingly, a missing standard deviation or mean for example can be calcuted if the p-value or confidence interval is presented. (studyresult.com)
Proportion15
- Confidence Intervals for a Simple Binomial Proportion. (routledge.com)
- Conditions for a z interval for a proportion Get 3 of 4 questions to level up! (khanacademy.org)
- In statistics, a binomial proportion confidence interval is a confidence interval for the probability of success calculated from the outcome of a series of success-failure experiments (Bernoulli trials). (wikipedia.org)
- In other words, a binomial proportion confidence interval is an interval estimate of a success probability p when only the number of experiments n and the number of successes nS are known. (wikipedia.org)
- Given this observed proportion, the confidence interval for the true probability of the coin landing on heads is a range of possible proportions, which may or may not contain the true proportion. (wikipedia.org)
- A 95% confidence interval for the proportion, for instance, will contain the true proportion 95% of the times that the procedure for constructing the confidence interval is employed. (wikipedia.org)
- Now I'd like to state a 95% confidence interval for what the proportion of the trait is in the population of turtles (which is pretty large). (r-bloggers.com)
- theta_true) ##Proportion of intervals covering the true value. (r-bloggers.com)
- Which of the following statements best describes the uncertainty associated with a 95% confidence interval for a population proportion, computed from a simple random sample? (jiskha.com)
- 1/07/2012 · Best Answer: Since you said you know how to find the intervals, I'll say that remember you add and subtract the SAME number to the sample proportion mean to get the interval. (dcevolution.net)
- We then talk about how to find confidence intervals for one population proportion. (dcevolution.net)
- In clinical trials, among 4482 patients treated with the drug, 197 developed the adverse reaction o nausea Construct a 90% confidence interval or the proportion of adverse reactions. (dcevolution.net)
- Given the true proportion p in the population, you could then determine how likely it is to get a sample proportion p̂ within various intervals. (dcevolution.net)
- Instructions: Use this step-by-step Confidence Interval for Proportion Calculator, by providing the sample data in the form below: Number of favorable cases \((X)\) = Sample. (mathcracker.com)
- This lesson describes how to create a confidence interval for a population proportion. (electronicsproductionworld.com)
Estimators2
- Some robust estimators against outliers are also considered to construct confidence intervals that are more resistant to outliers than the Student t confidence interval. (scialert.net)
- The confidence intervals of these estimators are computed and compared with each other for normal and contaminated normal data to determine which is better. (scialert.net)
Simple linear reg1
- The confidence interval for the slope of a simple linear regression equation uses the same general approach. (stattrek.com)
Inference6
- Inference on Regressions with Interval Data on a Regressor or Outcome ," Econometrica , Econometric Society, vol. 70(2), pages 519-546, March. (repec.org)
- Inference by eye: confidence intervals and how to read pictures of data. (nih.gov)
- Comparing Two Proportions Suppose you have two populations from … super mario nintendo ds how to get to world 4 This lesson starts with the basic concept of using confidence intervals to understand and perform inference. (dcevolution.net)
- On the tail of our previous paper about confidence intervals, showing that researchers tend to misunderstand the inferences one can draw from CIs, we [Morey, Rink Hoekstra, Jeffrey Rouder, Michael Lee, and EJ Wagenmakers] have another paper that we have just submitted which talks about the theory underlying inference by CIs. (andrewgelman.com)
- Having shown that standard Bayes and non-Bayes intervals line up for the student t situation, you write that "If researchers were only expected to study phenomena that were normally distributed […] then inference by confidence procedures might seem indistinguishable from inference by Bayesian procedures. (andrewgelman.com)
- Week 5&6: Introduction to Inference Week 5&6: Introduction to Inference Confidence Intervals In statistics, when we cannot get information from the entire population, we take a sample. (coursehero.com)
Hypothesis13
- Hypothesis Tests and Confidence Intervals. (routledge.com)
- The use of overlapping confidence intervals to determine significant differences between two rates presented in the Data Visualizations tool is discouraged because the practice fails to detect significant differences more frequently than standard hypothesis testing. (cdc.gov)
- An important theoretical derivation of this confidence interval involves the inversion of a hypothesis test. (wikipedia.org)
- Revision Free Essay: Confidence intervals and hypothesis testing with FREE Formatting included! (mit.edu)
- Where does this influence the way hypothesis intervals confidence and testing english sentences are cited. (mit.edu)
- If your academic writing is needed, finally and intervals confidence hypothesis testing. (mit.edu)
- Your readers and more cities and even those who care for the widest population of these articles, using textual details testing hypothesis intervals confidence and and generic features such as the child's writing at museums and galleries creative writing is where atc is declining c variable cost output if we say demand is perfectly we can t succeed. (mit.edu)
- Such dis comfort is understandable, but shouldn't we admit that they will show a powerful hiring hypothesis and intervals confidence testing draw. (mit.edu)
- Testing the Tests: What Are the Impacts of Incorrect Assumptions When Applying Confidence Intervals or Hypothesis Tests to Compare Competing Forecasts? (ametsoc.org)
- Gilleland, E., A. S. Hering, T. L. Fowler, and B. G. Brown, 2018: Testing the Tests: What Are the Impacts of Incorrect Assumptions When Applying Confidence Intervals or Hypothesis Tests to Compare Competing Forecasts? (ametsoc.org)
- I agree, and I too have been pushing against the idea that confidence intervals resolve the well-known problems with null hypothesis significance testing. (andrewgelman.com)
- For another take on the precision fallacy (the idea that the width of a confidence interval is a measure of the precision of an estimate), see my post , "Why it doesn't make sense in general to form confidence intervals by inverting hypothesis tests. (andrewgelman.com)
- Methods for calculating these confidence intervals have been developed that are based on inverting hypothesis tests using generalised heterogeneity statistics. (biomedcentral.com)
Calculating5
- Here the experimenter sets out the way in which they intend to calculate a confidence interval and to know, before they do the actual experiment, that the interval they will end up calculating has a particular chance of covering the true but unknown value. (wikipedia.org)
- Drawing on his extensive work as a statistician and professor at Cardiff University School of Medicine, the author brings together methods for calculating confidence intervals for proportions and several other important measures, including differences, ratios, and nonparametric effect size measures generalizing Mann-Whitney and Wilcoxon tests. (routledge.com)
- The performance of these confidence intervals is evaluated and compared by calculating the estimated coverage probability, the average width and the standard error by using simulation. (scialert.net)
- Hence the use of unequal tails when calculating confidence intervals using the methods we use here is not methodologically novel, but to our knowledge this paper is the first to investigate this particular issue in detail. (biomedcentral.com)
- Here is an simple example of calculating the 95% confidence interval … how to create a binary options platform I'm trying to calculate the confidence interval for the mean value using the method of bootstrap in python. (electronicsproductionworld.com)
Logistic regression2
- Appendix D. Coefficients (β) and 95% confidence intervals (CI) from multinomial logistic regression (mlogit) models of mosquito and black fly activity and from logistic regression model of oestrid presence on the Bathurst caribou post-calving and summer range, Northwest Territories and Nunavut, Canada. (figshare.com)
- My colleague therefore also performed the logistic regression using Medcalc (with the same database) which resulted in the same OR of 1.097 and same p-value of .001, but in slightly different confidence intervals (1.0373 - 1.1595). (talkstats.com)
Proportions5
- Confidence Intervals for Proportions and Related Measures of Effect Size illustrates the use of effect size measures and corresponding confidence intervals as more informative alternatives to the most basic and widely used significance tests. (routledge.com)
- This topic covers confidence intervals for means and proportions. (khanacademy.org)
- This routine calculates the group sample sizes necessary to achieve a specified interval width of the difference, ratio, or odds ratio of two independent proportions. (dcevolution.net)
- If the sample proportions are different from th ose specified when running the se procedures, the interval width may be narrower or wider than specified. (dcevolution.net)
- Technical Details A background of the comparison of two proportions is given, followed by details of the confidence interval methods available in this procedure. (dcevolution.net)
Interpretation7
- The practical interpretation of the interval is used for a single sampling. (kean.edu)
- What should be the role of P -values and confidence intervals in the interpretation of scientific results? (lww.com)
- The correct interpretation is thus that the confidence interval is constructed by a procedure, which, when you repeat the experiment many many times, is such that in 95% of the experiments the corresponding confidence interval would cover the true value. (r-bloggers.com)
- 7/10/2012 · The interpretation of a self belief interval is a elaborate factor to snatch for scholars taking a stats course. (dcevolution.net)
- I'll start with a simple illustration and show how that pertains to the fashioned interpretation of a ninety five% self belief interval for the actual mean. (dcevolution.net)
- The proper interpretation is that, if we draw many, many random samples of sample size n from a population, and compute the confidence interval around x-bar (the sample mean), then in the long run, 95% of the confidence intervals will contain the true population mean. (talkstats.com)
- For more details about the confidence intervals and their interpretation, see this explanation . (stlouisfed.org)
Asymptotic confidence intervals1
- Nelson (1995) presents a methodology to obtain asymptotic confidence intervals for the cost and the number of cumulative recurrent events. (scielo.br)
Probabilities of Default1
- In this paper we conduct a systematic comparison of confidence intervals around estimated probabilities of default (PD) using several analytical approaches as well as parametric and nonparametric bootstrap methods. (ssrn.com)
Significance5
- On judging the significance of differences by examining the overlap between confidence intervals. (cdc.gov)
- Epidemiologists who see no purpose to a confidence interval other than its use in significance testing sometimes wonder why this shift in reporting practice has occurred. (lww.com)
- and, the relationship between confidence interval and significance testing frameworks, particularly regarding power. (sagepub.com)
- This expertly written textbook adopts a pioneering approach to ANOVA with an emphasis on confidence intervals rather than tests of significance. (sagepub.com)
- So, like traditional significance testing, if 0 or 1.0 is inside the confidence interval (CI), there is no significant difference between the treatments. (nysora.com)
Calculate confidence7
- Instructor] Now, we'll learn how to calculate…confidence intervals. (lynda.com)
- In addition, it can be a better alternative than asymptotic-based methods to calculate confidence intervals, according to some Monte Carlo simulations. (scielo.br)
- Nelson (1988, 1995) presented a non parametric procedure to calculate confidence intervals for this function. (scielo.br)
- Two methods to calculate confidence limits for the MCF are presented in Section 3, the Nelson asymptotic procedure and our proposed technique. (scielo.br)
- In a gem of a paper (and here ) that sparkles with insight, the authors (Wagner, Hastie and Efron) take considerable care to make things clear to the reader while showing how to calculate confidence intervals for Random Forests models. (r-bloggers.com)
- Let us learn how to calculate confidence interval for population mean using in-built CONFIDENCE function in excel. (assignmenthelp.net)
- In this study, we calculate confidence intervals for the mean of a normal data and a contaminated normal data. (scialert.net)
Narrower2
- We saw indication that the likelihood ratio interval had better coverage and narrower intervals. (mdpi.com)
- A bootstrap calculation could be used to determine a confidence interval narrower than that calculated from σ, and so obtain some benefit from a large amount of extra work. (wikipedia.org)
Calculates2
- Calculates the confidence interval of the best power fit for an input data set. (ni.com)
- Calculates p-values and confidence intervals from descriptive (summary) statistics. (studyresult.com)
Upper bound7
- Upper bound of the confidence interval. (ni.com)
- Two examples show a substantial improvement (reduction) in the length and the minimum upper bound of the confidence intervals at the optimal level of the financial accounting variables. (defaultrisk.com)
- Control of Corruption: Percentile Rank, Upper Bound of 90% Confidence Interval in Haiti was reported at 12.98 % in 2019, according to the World Bank collection of development indicators, compiled from officially recognized sources. (tradingeconomics.com)
- Haiti - Control of Corruption: Percentile Rank, Upper Bound of 90% Confidence Interval - actual values, historical data, forecasts and projections were sourced from the World Bank on September of 2021. (tradingeconomics.com)
- Percentile Rank Upper refers to upper bound of 90 percent confidence interval for governance, expressed in percentile rank terms. (tradingeconomics.com)
- For example, if we constructed a 99% confidence interval with a lower bound of 52 and an upper bound of 71, we would interpret the interval as follows: "We are 99% confident that the population mean, , is between 52 and 71. (slideserve.com)
- A confidence interval is a range of values, from the lower bound to the respective upper bound, that describes the uncertainty surrounding an estimate. (stlouisfed.org)
Formulas1
- There are several formulas for a binomial confidence interval, but all of them rely on the assumption of a binomial distribution. (wikipedia.org)
Statistics8
- Confidence intervals were introduced to statistics by Jerzy Neyman in a paper published in 1937. (wikipedia.org)
- In statistics a robust confidence interval is a robust modification of confidence intervals, meaning that one modifies the non-robust calculations of the confidence interval so that they are not badly affected by outlying or aberrant observations in a data-set. (wikipedia.org)
- One, we should work harder than ever to avoid strict or exact interpretations of P -values and confidence intervals in observational research, where these statistics lack a theoretical basis. (lww.com)
- This is the first book to introduce the new statistics - effect sizes, confidence intervals, and meta-analysis - in an accessible way. (routledge.com)
- well designed as an introductory text to confidence intervals, effect sizes and meta-analyses for use by teachers and students of statistics. (routledge.com)
- Confidence intervals for the between-study variance in random-effects meta-analysis using generalised heterogeneity statistics: should we use unequal tails? (biomedcentral.com)
- We conclude that using unequal tail probabilities when computing 95 % confidence intervals for the between-study variance, when using methods based on generalised heterogeneity statistics, can result in shorter confidence intervals. (biomedcentral.com)
- Using Excel you can quickly and easily calculate the confidence statistics you need. (electronicsproductionworld.com)
Directly standardized rates2
- Confidence intervals for directly standardized rates: a method based on the gamma distribution. (cdc.gov)
- We offer an approximation to central confidence intervals for directly standardized rates, where we assume that the rates are distributed as a weighted sum of independent Poisson random variables. (cdc.gov)
Interpret confidence intervals1
- How to Interpret Confidence Intervals. (electronicsproductionworld.com)
Likelihood-based confidence intervals2
- Herein, we aim to investigate the performance of likelihood-based confidence intervals when only minimum-maximum and sample size is available. (mdpi.com)
- We then propose two new empirical likelihood-based confidence intervals for the sensitivity of the test at a fixed level of specificity by using the scaled chi-square distribution. (ebscohost.com)
Estimator1
- Our estimator makes few assumptions about the underlying neural dynamics, shows excellent performance in experimentally relevant regimes, and uniquely provides confidence intervals bounding the range of information rates compatible with the observed spike train. (mit.edu)
Compute the 953
- a) Compute the 95 % confidence interval for the population mean. (jiskha.com)
- In other words, if we have a sample mean of 10.2, and we compute the 95% confidence interval to be (9.65, 10.75), we CANNOT say that there is a .95 probability that the true population mean is within (9.65, 10.75). (talkstats.com)
- but their main purpose is to compute the 95% confidence intervals. (powerofcharismabook.com)
Distributions1
- z and t distributions are used in confidence intervals. (slideserve.com)
Odds ratio7
- Howdy everyone I'm trying to get Odds ratio and OR confidence intervals using a probit model, but I'm not getting. (ethz.ch)
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- My current favorite (hypothetical) example is an epidemiology study of some small effect where the point estimate of the odds ratio is 3.0 with a 95% conf interval of [1.1, 8.2]. (andrewgelman.com)
- The confidence level is the probability that the confidence interval contains the true odds ratio. (electronicsproductionworld.com)
- The higher the confidence level the more certain you can be that the interval contains the true odds ratio. (electronicsproductionworld.com)
Approximate 951
- Using Monte Carlo simulation, we looked at the confidence interval coverage characteristics for likelihood ratio and Wald-type approximate 95% confidence intervals. (mdpi.com)
Procedure2
- A confidence interval constructing procedure yields a random interval, because it depends on quantities (in particular \(x\) ), which are random. (r-bloggers.com)
- we computed above is thus just one of many possible confidence intervals originating from above procedure. (r-bloggers.com)
Degrees of free1
- Because it is assumed that σ is unknown, this will be a t-interval with 40 degrees of freedom and s = 24.77. (slideserve.com)
Resulting intervals are usually2
- Although this method requires much weaker assumptions than those required by the classical methods, the resulting intervals are usually too large. (hindawi.com)
- Whilst, under the random effects model, these new methods furnish confidence intervals with the correct coverage, the resulting intervals are usually very wide, making them uninformative. (biomedcentral.com)
Methods11
- Evaluation of Performance of Confidence Interval Methods. (routledge.com)
- Widening the Applicability of Confidence Interval Methods: The Propagating Imprecision Approach. (routledge.com)
- In this context, computer-intensive methods such as bootstrap can be used to construct confidence intervals. (scielo.br)
- Finally, we provide some simulation results comparing these methods with respect to their empirical coverage accuracy and average interval length. (hindawi.com)
- The confidence intervals based on exponential type inequalities have a guaranteed coverage probability under much weaker assumptions than required by the standard methods. (hindawi.com)
- Although the obtained confidence intervals are usually too large, there are situations when they give better coverage accuracy than the classical methods. (hindawi.com)
- We calculate the confidence intervals of the error rate using both parametric and non-parametric methods. (nist.gov)
- What we found from the evaluation result is that there is no significant difference of the computed Confidence Intervals by all three methods. (nist.gov)
- Since the early 1980s, a bewildering array of methods for constructing bootstrap confidence intervals have been proposed. (nih.gov)
- In order to do this, we review the common algorithms for resampling and methods for constructing bootstrap confidence intervals, together with some less well known ones, highlighting their strengths and weaknesses. (nih.gov)
- The gamma intervals perform at least as well as existing methods in all situations studied here, but perform especially better than existing methods when the number of counts in any specific cell is small and there is large variability in the weights. (cdc.gov)
1.962
- displaystyle \overline{X} +/- 1.96 \frac{s}{\sqrt{n}}$ is a CI at the 95% confidence level. (mathhelpforum.com)
- The Z for a 95% confidence interval (Z.95) is 1.96, as can be found using the normal distribution calculator (setting the shaded area to .95 and clicking on the "Between" button). (electronicsproductionworld.com)
Construct a confidence interval5
- This lesson describes how to construct a confidence interval around the slope of a regression line. (stattrek.com)
- To construct a confidence interval for the slope of the regression line, we need to know the standard error of the sampling distribution of the slope. (stattrek.com)
- In the next section, we work through a problem that shows how to use this approach to construct a confidence interval for the slope of a regression line. (stattrek.com)
- The correct answer is (C). Use the following four-step approach to construct a confidence interval. (stattrek.com)
- 30, it is not necessary to assume that the costs follow a normal distribution to construct a confidence interval. (slideserve.com)
Level23
- The confidence level is designated prior to examining the data. (wikipedia.org)
- Most commonly, the 95% confidence level is used. (wikipedia.org)
- Factors affecting the width of the confidence interval include the size of the sample, the confidence level, and the variability in the sample. (wikipedia.org)
- A higher confidence level will tend to produce a broader confidence interval. (wikipedia.org)
- An interval estimate provides more information about a population characteristic than does a point estimate and therefore provides a confidence level for the estimate. (lynda.com)
- Confidence intervals that are expected to include the true underlying rate 95% of the time are used in the Data Visualizations tool and are modified gamma intervals 3 computed using SEER*Stat. external icon The modified gamma intervals are more efficient than the gamma intervals of Fay and Feuer 4 in that they are less conservative while still retaining the nominal coverage level. (cdc.gov)
- Finding the critical value z* for a desired confidence level Get 3 of 4 questions to level up! (khanacademy.org)
- Sample size and margin of error in a z interval for p Get 3 of 4 questions to level up! (khanacademy.org)
- Surprisingly, even with these relatively tight confidence intervals, it is impossible to distinguish notch-level PDs for investment grade ratings, e.g. a PDAA- from a PDA+. (ssrn.com)
- If we were to use a table to look up t at the 95% confidence level, we would look the t value corresponding to a = (1-95%) = 0.025. (stfx.ca)
- Level of certainty for the confidence interval. (ni.com)
- confidence level must be greater than 0 and less than 1. (ni.com)
- Select a confidence level. (stattrek.com)
- The confidence level describes the uncertainty of a sampling method. (stattrek.com)
- And the uncertainty is denoted by the confidence level. (stattrek.com)
- In this analysis, the confidence level is defined for us in the problem. (stattrek.com)
- We are working with a 99% confidence level. (stattrek.com)
- The value for z is found from standard normal distribution tables for a given confidence level right here . (study.com)
- Use the given confidence level and sample data to find a confidence interval for the population standard sigma. (jiskha.com)
- Show transcribed image text Use the sample data and confidence level given below to complete parts (a) through (d). (dcevolution.net)
- Level of confidence: As the level of confidence increases, the margin of error also increases. (slideserve.com)
- This percentage is the confidence level. (electronicsproductionworld.com)
- The "90%" in the confidence interval listed above represents a level of certainty about our estimate. (stlouisfed.org)
Anova1
- Student-focused throughout, it offers a comprehensive introduction to ANOVA using confidence intervals. (sagepub.com)
Linear Regression1
- Is it remotely legitimate to use the standard errors of the coefficients from linear regression in a Monte Carlo simulation to bootstrap 2.5%/97.5% confidence intervals on the predictions? (talkstats.com)
Data4
- Based on the (usually taken) assumption that observed data are random samples from a true population, the confidence interval obtained from the data is also random. (wikipedia.org)
- The width of a confidence interval depends on the amount of variability in the data. (cdc.gov)
- object that contains the computed confidence interval data. (mathworks.com)
- The size of this interval naturally depends on the type of data and its distribution. (explorable.com)
Lesson1
- In this lesson, we are going to focus on the first two cases where we use the normal distribution to make the confidence interval for mu. (study.com)
Sample20
- Confidence intervals give us a range of plausible values for some unknown value based on results from a sample. (khanacademy.org)
- Then report the confidence intervals from all three approaches, with different sample sizes. (nist.gov)
- Dorey, F. J. and Korn, E. L. (1987), Effective sample sizes for confidence intervals for survival probabilities. (wiley.com)
- The range of the confidence interval is defined by the sample statistic + margin of error . (stattrek.com)
- We find that the gamma intervals remain conservative while the DKES intervals and the ABC intervals become anti-conservative as the sample variance of the weights increases. (cdc.gov)
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- Simulation studies are conducted to compare the finite sample performance of the newly proposed intervals with the existing intervals for the sensitivity in terms of coverage probability. (ebscohost.com)
- If we took a hundred samples, we would expect that about 95 sample means would be within this interval. (coursehero.com)
- This part of ASQ/ANSI/ISO 16269 specifies the procedures for establishing a point estimate and confidence intervals for the median of any continuous probability distribution of a population, based on a random sample size from the population. (asq.org)
- In order to be able to generalize [4] this to the whole university group, you will need a confidence interval that reflects the applicability of this result for the given sample of students to the whole university. (explorable.com)
Depends1
- that the coverage of LOD support intervals depends upon the effect of the QTL, and so they do not behave as true confidence intervals. (genetics.org)
Calculation of a confidence interval1
- Once such a QTL has been identified, interest turns to the calculation of a confidence interval for its location, as such an interval estimate can be a useful guide for the design of further experiments, such as the generation of congenic lines. (genetics.org)
Bayes2
- Likelihood support intervals and approximate Bayes credible intervals, on the other hand, are shown to behave appropriately. (genetics.org)
- But if you slap on a flat prior you get a Bayes 95% posterior interval of [1.1, 8.2] which will not in general make sense, because real-world odds ratios are much more likely to be near 1.1 than to be near 8.2. (andrewgelman.com)
Conceptually different1
- Here, we introduce a conceptually different type of confidence interval. (repec.org)
Examples1
- Before we get into examples of the confidence interval, a short comment about interpreting what a confidence interval is. (talkstats.com)
Empirical2
- The confidence intervals obtained by the empirical likelihood method have some very appealing characteristics. (hindawi.com)
- Empirical likelihood intervals are Bartlett correctable in most cases. (hindawi.com)
Bootstrap method1
- For the non-parametric approach, we use the bootstrap method to compute the confidence intervals directly. (nist.gov)
Prediction intervals2
- The method is applied to the problem of obtaining confidence and prediction intervals for manually-calibrated ground-water flow models. (usgs.gov)
- A simple Monte Carlo method is used to compute the quantiles necessary to establish probability levels for the confidence and prediction intervals. (usgs.gov)
Find a confidence interval1
- To find a confidence interval, you simply run that backward. (dcevolution.net)
Commonly2
- A commonly used formula for a binomial confidence interval relies on approximating the distribution of error about a binomially-distributed observation, p ^ {\displaystyle {\hat {p}}} , with a normal distribution. (wikipedia.org)
- We describe here a method for determining confidence intervals for a commonly used index of diversity. (asm.org)