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.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.Risk Factors: An aspect of personal behavior or lifestyle, environmental exposure, or inborn or inherited characteristic, which, on the basis of epidemiologic evidence, is known to be associated with a health-related condition considered important to prevent.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.Cross-Sectional Studies: Studies in which the presence or absence of disease or other health-related variables are determined in each member of the study population or in a representative sample at one particular time. This contrasts with LONGITUDINAL STUDIES which are followed over a period of time.Multivariate Analysis: A set of techniques used when variation in several variables has to be studied simultaneously. In statistics, multivariate analysis is interpreted as any analytic method that allows simultaneous study of two or more dependent variables.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.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.Prospective Studies: Observation of a population for a sufficient number of persons over a sufficient number of years to generate incidence or mortality rates subsequent to the selection of the study group.Prevalence: The total number of cases of a given disease in a specified population at a designated time. It is differentiated from INCIDENCE, which refers to the number of new cases in the population at a given time.Questionnaires: Predetermined sets of questions used to collect data - clinical data, social status, occupational group, etc. The term is often applied to a self-completed survey instrument.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.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.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.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.Socioeconomic Factors: Social and economic factors that characterize the individual or group within the social structure.Risk Assessment: The qualitative or quantitative estimation of the likelihood of adverse effects that may result from exposure to specified health hazards or from the absence of beneficial influences. (Last, Dictionary of Epidemiology, 1988)Time Factors: Elements of limited time intervals, contributing to particular results or situations.Follow-Up Studies: Studies in which individuals or populations are followed to assess the outcome of exposures, procedures, or effects of a characteristic, e.g., occurrence of disease.Treatment Outcome: Evaluation undertaken to assess the results or consequences of management and procedures used in combating disease in order to determine the efficacy, effectiveness, safety, and practicability of these interventions in individual cases or series.United StatesSmoking: Inhaling and exhaling the smoke of burning TOBACCO.Prognosis: A prediction of the probable outcome of a disease based on a individual's condition and the usual course of the disease as seen in similar situations.JapanSeverity of Illness Index: Levels within a diagnostic group which are established by various measurement criteria applied to the seriousness of a patient's disorder.ROC Curve: A graphic means for assessing the ability of a screening test to discriminate between healthy and diseased persons; may also be used in other studies, e.g., distinguishing stimuli responses as to a faint stimuli or nonstimuli.Pregnancy: The status during which female mammals carry their developing young (EMBRYOS or FETUSES) in utero before birth, beginning from FERTILIZATION to BIRTH.Linear Models: Statistical models in which the value of a parameter for a given value of a factor is assumed to be equal to a + bx, where a and b are constants. The models predict a linear regression.China: A country spanning from central Asia to the Pacific Ocean.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.Confidence Intervals: A range of values for a variable of interest, e.g., a rate, constructed so that this range has a specified probability of including the true value of the variable.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)Incidence: The number of new cases of a given disease during a given period in a specified population. It also is used for the rate at which new events occur in a defined population. It is differentiated from PREVALENCE, which refers to all cases, new or old, in the population at a given time.Infant, Newborn: An infant during the first month after birth.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.Health Surveys: A systematic collection of factual data pertaining to health and disease in a human population within a given geographic area.Longitudinal Studies: Studies in which variables relating to an individual or group of individuals are assessed over a period of time.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.Educational Status: Educational attainment or level of education of individuals.Genotype: The genetic constitution of the individual, comprising the ALLELES present at each GENETIC LOCUS.Epidemiologic Methods: Research techniques that focus on study designs and data gathering methods in human and animal populations.Genetic Predisposition to Disease: A latent susceptibility to disease at the genetic level, which may be activated under certain conditions.Asian Continental Ancestry Group: Individuals whose ancestral origins are in the southeastern and eastern areas of the Asian continent.European Continental Ancestry Group: Individuals whose ancestral origins are in the continent of Europe.Sensitivity and Specificity: Binary classification measures to assess test results. Sensitivity or recall rate is the proportion of true positives. Specificity is the probability of correctly determining the absence of a condition. (From Last, Dictionary of Epidemiology, 2d ed)Sex Distribution: The number of males and females in a given population. The distribution may refer to how many men or women or what proportion of either in the group. The population is usually patients with a specific disease but the concept is not restricted to humans and is not restricted to medicine.Risk: The probability that an event will occur. It encompasses a variety of measures of the probability of a generally unfavorable outcome.Netherlands: Country located in EUROPE. It is bordered by the NORTH SEA, BELGIUM, and GERMANY. Constituent areas are Aruba, Curacao, Sint Maarten, formerly included in the NETHERLANDS ANTILLES.Age Distribution: The frequency of different ages or age groups in a given population. The distribution may refer to either how many or what proportion of the group. The population is usually patients with a specific disease but the concept is not restricted to humans and is not restricted to medicine.Health Status: The level of health of the individual, group, or population as subjectively assessed by the individual or by more objective measures.TaiwanRural Population: The inhabitants of rural areas or of small towns classified as rural.Social Class: A stratum of people with similar position and prestige; includes social stratification. Social class is measured by criteria such as education, occupation, and income.Alcohol Drinking: Behaviors associated with the ingesting of alcoholic beverages, including social drinking.African Americans: Persons living in the United States having origins in any of the black groups of Africa.Demography: Statistical interpretation and description of a population with reference to distribution, composition, or structure.Urban Population: The inhabitants of a city or town, including metropolitan areas and suburban areas.Analysis of Variance: A statistical technique that isolates and assesses the contributions of categorical independent variables to variation in the mean of a continuous dependent variable.Polymorphism, Single Nucleotide: A single nucleotide variation in a genetic sequence that occurs at appreciable frequency in the population.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).Health Knowledge, Attitudes, Practice: Knowledge, attitudes, and associated behaviors which pertain to health-related topics such as PATHOLOGIC PROCESSES or diseases, their prevention, and treatment. This term refers to non-health workers and health workers (HEALTH PERSONNEL).Hospital Mortality: A vital statistic measuring or recording the rate of death from any cause in hospitalized populations.Republic of Korea: The capital is Seoul. The country, established September 9, 1948, is located on the southern part of the Korean Peninsula. Its northern border is shared with the Democratic People's Republic of Korea.Residence Characteristics: Elements of residence that characterize a population. They are applicable in determining need for and utilization of health services.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.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.BrazilRegistries: The systems and processes involved in the establishment, support, management, and operation of registers, e.g., disease registers.Depression: Depressive states usually of moderate intensity in contrast with major depression present in neurotic and psychotic disorders.Hypertension: Persistently high systemic arterial BLOOD PRESSURE. Based on multiple readings (BLOOD PRESSURE DETERMINATION), hypertension is currently defined as when SYSTOLIC PRESSURE is consistently greater than 140 mm Hg or when DIASTOLIC PRESSURE is consistently 90 mm Hg or more.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)Postoperative Complications: Pathologic processes that affect patients after a surgical procedure. They may or may not be related to the disease for which the surgery was done, and they may or may not be direct results of the surgery.Hospitalization: The confinement of a patient in a hospital.Proportional Hazards Models: Statistical models used in survival analysis that assert that the effect of the study factors on the hazard rate in the study population is multiplicative and does not change over time.Life Style: Typical way of life or manner of living characteristic of an individual or group. (From APA, Thesaurus of Psychological Index Terms, 8th ed)Hispanic Americans: Persons living in the United States of Mexican (MEXICAN AMERICANS), Puerto Rican, Cuban, Central or South American, or other Spanish culture or origin. The concept does not include Brazilian Americans or Portuguese Americans.NorwayHIV Infections: Includes the spectrum of human immunodeficiency virus infections that range from asymptomatic seropositivity, thru AIDS-related complex (ARC), to acquired immunodeficiency syndrome (AIDS).Occupational Exposure: The exposure to potentially harmful chemical, physical, or biological agents that occurs as a result of one's occupation.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)GermanySurvival 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.Disease Progression: The worsening of a disease over time. This concept is most often used for chronic and incurable diseases where the stage of the disease is an important determinant of therapy and prognosis.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.IndiaOccupational Diseases: Diseases caused by factors involved in one's employment.Breast Neoplasms: Tumors or cancer of the human BREAST.Data Collection: Systematic gathering of data for a particular purpose from various sources, including questionnaires, interviews, observation, existing records, and electronic devices. The process is usually preliminary to statistical analysis of the data.Survival Rate: The proportion of survivors in a group, e.g., of patients, studied and followed over a period, or the proportion of persons in a specified group alive at the beginning of a time interval who survive to the end of the interval. It is often studied using life table methods.Models, Statistical: Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc.Employment: The state of being engaged in an activity or service for wages or salary.ItalyCoronary Artery Disease: Pathological processes of CORONARY ARTERIES that may derive from a congenital abnormality, atherosclerotic, or non-atherosclerotic cause.Health Behavior: Behaviors expressed by individuals to protect, maintain or promote their health status. For example, proper diet, and appropriate exercise are activities perceived to influence health status. Life style is closely associated with health behavior and factors influencing life style are socioeconomic, educational, and cultural.Parity: The number of offspring a female has borne. It is contrasted with GRAVIDITY, which refers to the number of pregnancies, regardless of outcome.Self Report: Method for obtaining information through verbal responses, written or oral, from subjects.Gestational Age: The age of the conceptus, beginning from the time of FERTILIZATION. In clinical obstetrics, the gestational age is often estimated as the time from the last day of the last MENSTRUATION which is about 2 weeks before OVULATION and fertilization.Ethnic Groups: A group of people with a common cultural heritage that sets them apart from others in a variety of social relationships.Probability: The study of chance processes or the relative frequency characterizing a chance process.Stress, Psychological: Stress wherein emotional factors predominate.SwedenDenmarkPatient Acceptance of Health Care: The seeking and acceptance by patients of health service.FinlandMaternal Age: The age of the mother in PREGNANCY.Substance-Related Disorders: Disorders related to substance abuse.Spain: Parliamentary democracy located between France on the northeast and Portugual on the west and bordered by the Atlantic Ocean and the Mediterranean Sea.Recurrence: The return of a sign, symptom, or disease after a remission.Marital Status: A demographic parameter indicating a person's status with respect to marriage, divorce, widowhood, singleness, etc.Occupations: Crafts, trades, professions, or other means of earning a living.CaliforniaDiet: Regular course of eating and drinking adopted by a person or animal.TexasInterviews as Topic: Conversations with an individual or individuals held in order to obtain information about their background and other personal biographical data, their attitudes and opinions, etc. It includes school admission or job interviews.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.Sexual Behavior: Sexual activities of humans.Family Characteristics: Size and composition of the family.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)Diabetes Mellitus: A heterogeneous group of disorders characterized by HYPERGLYCEMIA and GLUCOSE INTOLERANCE.Mass Screening: Organized periodic procedures performed on large groups of people for the purpose of detecting disease.Risk-Taking: Undertaking a task involving a challenge for achievement or a desirable goal in which there is a lack of certainty or a fear of failure. It may also include the exhibiting of certain behaviors whose outcomes may present a risk to the individual or to those associated with him or her.Income: Revenues or receipts accruing from business enterprise, labor, or invested capital.Health Services Accessibility: The degree to which individuals are inhibited or facilitated in their ability to gain entry to and to receive care and services from the health care system. Factors influencing this ability include geographic, architectural, transportational, and financial considerations, among others.Blood Pressure: PRESSURE of the BLOOD on the ARTERIES and other BLOOD VESSELS.C-Reactive Protein: A plasma protein that circulates in increased amounts during inflammation and after tissue damage.TurkeyPregnancy Outcome: Results of conception and ensuing pregnancy, including LIVE BIRTH; STILLBIRTH; SPONTANEOUS ABORTION; INDUCED ABORTION. The outcome may follow natural or artificial insemination or any of the various ASSISTED REPRODUCTIVE TECHNIQUES, such as EMBRYO TRANSFER or FERTILIZATION IN VITRO.Poverty: A situation in which the level of living of an individual, family, or group is below the standard of the community. It is often related to a specific income level.Population Surveillance: Ongoing scrutiny of a population (general population, study population, target population, etc.), generally using methods distinguished by their practicability, uniformity, and frequently their rapidity, rather than by complete accuracy.Quality of Life: A generic concept reflecting concern with the modification and enhancement of life attributes, e.g., physical, political, moral and social environment; the overall condition of a human life.Overweight: A status with BODY WEIGHT that is above certain standard of acceptable or desirable weight. In the scale of BODY MASS INDEX, overweight is defined as having a BMI of 25.0-29.9 kg/m2. Overweight may or may not be due to increases in body fat (ADIPOSE TISSUE), hence overweight does not equal "over fat".Adolescent Behavior: Any observable response or action of an adolescent.Cardiovascular Diseases: Pathological conditions involving the CARDIOVASCULAR SYSTEM including the HEART; the BLOOD VESSELS; or the PERICARDIUM.Canada: The largest country in North America, comprising 10 provinces and three territories. Its capital is Ottawa.Health Care Surveys: Statistical measures of utilization and other aspects of the provision of health care services including hospitalization and ambulatory care.Length of Stay: The period of confinement of a patient to a hospital or other health facility.Urban Health: The status of health in urban populations.Students: Individuals enrolled in a school or formal educational program.Myocardial Infarction: NECROSIS of the MYOCARDIUM caused by an obstruction of the blood supply to the heart (CORONARY CIRCULATION).Anthropometry: The technique that deals with the measurement of the size, weight, and proportions of the human or other primate body.Outcome Assessment (Health Care): Research aimed at assessing the quality and effectiveness of health care as measured by the attainment of a specified end result or outcome. Measures include parameters such as improved health, lowered morbidity or mortality, and improvement of abnormal states (such as elevated blood pressure).Ethiopia: An independent state in eastern Africa. Ethiopia is located in the Horn of Africa and is bordered on the north and northeast by Eritrea, on the east by Djibouti and Somalia, on the south by Kenya, and on the west and southwest by Sudan. Its capital is Addis Ababa.Mothers: Female parents, human or animal.Workplace: Place or physical location of work or employment.Acute Disease: Disease having a short and relatively severe course.African Continental Ancestry Group: Individuals whose ancestral origins are in the continent of Africa.Health Status Indicators: The measurement of the health status for a given population using a variety of indices, including morbidity, mortality, and available health resources.Gene Frequency: The proportion of one particular in the total of all ALLELES for one genetic locus in a breeding POPULATION.Activities of Daily Living: The performance of the basic activities of self care, such as dressing, ambulation, or eating.Attitude to Health: Public attitudes toward health, disease, and the medical care system.Reference Values: The range or frequency distribution of a measurement in a population (of organisms, organs or things) that has not been selected for the presence of disease or abnormality.Social Support: Support systems that provide assistance and encouragement to individuals with physical or emotional disabilities in order that they may better cope. Informal social support is usually provided by friends, relatives, or peers, while formal assistance is provided by churches, groups, etc.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.Forecasting: The prediction or projection of the nature of future problems or existing conditions based upon the extrapolation or interpretation of existing scientific data or by the application of scientific methodology.Alleles: Variant forms of the same gene, occupying the same locus on homologous CHROMOSOMES, and governing the variants in production of the same gene product.Environmental Exposure: The exposure to potentially harmful chemical, physical, or biological agents in the environment or to environmental factors that may include ionizing radiation, pathogenic organisms, or toxic chemicals.Statistics as Topic: The science and art of collecting, summarizing, and analyzing data that are subject to random variation. The term is also applied to the data themselves and to the summarization of the data.Coronary Disease: An imbalance between myocardial functional requirements and the capacity of the CORONARY VESSELS to supply sufficient blood flow. It is a form of MYOCARDIAL ISCHEMIA (insufficient blood supply to the heart muscle) caused by a decreased capacity of the coronary vessels.Tomography, X-Ray Computed: Tomography using x-ray transmission and a computer algorithm to reconstruct the image.Intensive Care Units: Hospital units providing continuous surveillance and care to acutely ill patients.Birth Weight: The mass or quantity of heaviness of an individual at BIRTH. It is expressed by units of pounds or kilograms.Breast Feeding: The nursing of an infant at the breast.Neoplasm Regression, Spontaneous: Disappearance of a neoplasm or neoplastic state without the intervention of therapy.Continental Population Groups: Groups of individuals whose putative ancestry is from native continental populations based on similarities in physical appearance.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.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)Health Status Disparities: Variation in rates of disease occurrence and disabilities between population groups defined by socioeconomic characteristics such as age, ethnicity, economic resources, or gender and populations identified geographically or similar measures.Patient Compliance: Voluntary cooperation of the patient in following a prescribed regimen.Data Interpretation, Statistical: Application of statistical procedures to analyze specific observed or assumed facts from a particular study.Physician's Practice Patterns: Patterns of practice related to diagnosis and treatment as especially influenced by cost of the service requested and provided.Pregnancy Complications: Conditions or pathological processes associated with pregnancy. They can occur during or after pregnancy, and range from minor discomforts to serious diseases that require medical interventions. They include diseases in pregnant females, and pregnancies in females with diseases.Diabetes Complications: Conditions or pathological processes associated with the disease of diabetes mellitus. Due to the impaired control of BLOOD GLUCOSE level in diabetic patients, pathological processes develop in numerous tissues and organs including the EYE, the KIDNEY, the BLOOD VESSELS, and the NERVE TISSUE.Housing: Living facilities for humans.Aging: The gradual irreversible changes in structure and function of an organism that occur as a result of the passage of time.Coronary Angiography: Radiography of the vascular system of the heart muscle after injection of a contrast medium.Magnetic Resonance Imaging: Non-invasive method of demonstrating internal anatomy based on the principle that atomic nuclei in a strong magnetic field absorb pulses of radiofrequency energy and emit them as radiowaves which can be reconstructed into computerized images. The concept includes proton spin tomographic techniques.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)Rural Health: The status of health in rural populations.Delivery, Obstetric: Delivery of the FETUS and PLACENTA under the care of an obstetrician or a health worker. Obstetric deliveries may involve physical, psychological, medical, or surgical interventions.Parents: Persons functioning as natural, adoptive, or substitute parents. The heading includes the concept of parenthood as well as preparation for becoming a parent.Body Weight: The mass or quantity of heaviness of an individual. It is expressed by units of pounds or kilograms.MassachusettsPrenatal Care: Care provided the pregnant woman in order to prevent complications, and decrease the incidence of maternal and prenatal mortality.Algorithms: A procedure consisting of a sequence of algebraic formulas and/or logical steps to calculate or determine a given task.Neoplasm Staging: Methods which attempt to express in replicable terms the extent of the neoplasm in the patient.Healthcare Disparities: Differences in access to or availability of medical facilities and services.Haplotypes: The genetic constitution of individuals with respect to one member of a pair of allelic genes, or sets of genes that are closely linked and tend to be inherited together such as those of the MAJOR HISTOCOMPATIBILITY COMPLEX.Colorectal Neoplasms: Tumors or cancer of the COLON or the RECTUM or both. Risk factors for colorectal cancer include chronic ULCERATIVE COLITIS; FAMILIAL POLYPOSIS COLI; exposure to ASBESTOS; and irradiation of the CERVIX UTERI.Metabolic Syndrome X: A cluster of metabolic risk factors for CARDIOVASCULAR DISEASES and TYPE 2 DIABETES MELLITUS. The major components of metabolic syndrome X include excess ABDOMINAL FAT; atherogenic DYSLIPIDEMIA; HYPERTENSION; HYPERGLYCEMIA; INSULIN RESISTANCE; a proinflammatory state; and a prothrombotic (THROMBOSIS) state. (from AHA/NHLBI/ADA Conference Proceedings, Circulation 2004; 109:551-556)MexicoSexual Partners: Married or single individuals who share sexual relations.Age of Onset: The age, developmental stage, or period of life at which a disease or the initial symptoms or manifestations of a disease appear in an individual.Emigrants and Immigrants: People who leave their place of residence in one country and settle in a different country.Mental Disorders: Psychiatric illness or diseases manifested by breakdowns in the adaptational process expressed primarily as abnormalities of thought, feeling, and behavior producing either distress or impairment of function.Blood Glucose: Glucose in blood.Patient Selection: Criteria and standards used for the determination of the appropriateness of the inclusion of patients with specific conditions in proposed treatment plans and the criteria used for the inclusion of subjects in various clinical trials and other research protocols.Motor Activity: The physical activity of a human or an animal as a behavioral phenomenon.Mental Health: The state wherein the person is well adjusted.France: A country in western Europe bordered by the Atlantic Ocean, the English Channel, the Mediterranean Sea, and the countries of Belgium, Germany, Italy, Spain, Switzerland, the principalities of Andorra and Monaco, and by the duchy of Luxembourg. Its capital is Paris.Asthma: A form of bronchial disorder with three distinct components: airway hyper-responsiveness (RESPIRATORY HYPERSENSITIVITY), airway INFLAMMATION, and intermittent AIRWAY OBSTRUCTION. It is characterized by spasmodic contraction of airway smooth muscle, WHEEZING, and dyspnea (DYSPNEA, PAROXYSMAL).Self Concept: A person's view of himself.
Applied Logistic Regression. New York: Wiley. ISBN 978-0-470-58247-3. Alan Agresti (2012). Categorical Data Analysis. Hoboken: ... The expected number (from the logistic model) can be calculated using the equation from the logistic regression. These are ... The expected probability of success (a grade of A) is given by the equation for the logistic regression model: p ( s u c c e s ... Logistic regression models provide an estimate of the probability of an outcome, usually designated as a "success". It is ...
Regression analysis, Multiple regression analysis, Logistic regression is used as an estimate of criterion validity. Software ... These methods include Multiple Regression and Prediction; Moderated and Mediated Regression Analysis; Logistics Regression; ... Menard, S. (2001). Applied logistic regression analysis. (2nd ed.). Thousand Oaks. CA: Sage Publications. Tabachnick, B. G., & ... Menard, S. (2001). Applied logistic regression analysis. (2nd ed.). Thousand Oaks. CA: Sage Publications. Nunnally, J. & ...
Christensen, Ronald (1997). Log-linear models and logistic regression. Springer Texts in Statistics (Second ed.). New York: ... Bishop, Y. M. M.; Fienberg, S. E.; Holland, P. W. (1975). Discrete Multivariate Analysis: Theory and Practice. MIT Press. ISBN ... Ferguson, G. A. (1966). Statistical analysis in psychology and education. New York: McGraw-Hill. Smith, S. C., & Albaum, G. S ... ISBN 0-824-76698-9. On-line analysis of contingency tables: calculator with examples Interactive cross tabulation, chi-squared ...
Regression analysis on categorical outcomes is accomplished through multinomial logistic regression, multinomial probit or a ... as independent variables in a regression analysis or as dependent variables in logistic regression or probit regression, but ... and separate regression models (logistic regression, probit regression, etc.). As a result, the term "categorical variable" is ... Simple slopes analysis is a common post hoc test used in regression which is similar to the simple effects analysis in ANOVA, ...
Raju, N. S., Steinhaus, S. D., Edwards, J. E., & DeLessio, J. (1991). A logistic regression model for personnel selection. ... Raju, N. S., Burke, M. J., & Normand, J. (1990). A new approach for utility analysis. Journal of Applied Psychology, 75(1), 3- ... Raju, N. S., & Normand, J. (1985). The regression bias method: A unified approach for detecting item bias and selection bias. ... Raju, N. S., Burke, M. J., & Maurer, T. J. (1995). A note on direct range restriction corrections in utility analysis. ...
... logistic regression analysis [showed considerable] statistical uncertainty... The Victorian analysis of potential periodic ... An Analysis using Panel Data". 1999. JSTOR 1060816. We examined the effectiveness of state automobile safety inspections and ...
Naive Bayes (NB). Generalized linear model (GLM) for Logistic regression. Support Vector Machine (SVM). Decision Trees (DT). ... It contains several data mining and data analysis algorithms for classification, prediction, regression, associations, feature ... The PREDICT operation is used for predicting target values classification or regression while EXPLAIN ranks attributes in order ... One-class Support Vector Machine (SVM). Regression Support Vector Machine (SVM). Generalized linear model (GLM) for Multiple ...
"Predictive Factors for Postherpetic Neuralgia Using Ordered Logistic Regression Analysis". The Clinical Journal of Pain. 28 (8 ... a systematic analysis for the Global Burden of Disease Study 2015". Lancet. 388 (10053): 1459-1544. doi:10.1016/s0140-6736(16) ... a systematic analysis for the Global Burden of Disease Study 2013". Lancet. 386 (9995): 743-800. doi:10.1016/s0140-6736(15) ... a systematic analysis for the Global Burden of Disease Study 2013". Lancet. 385 (9963): 117-71. doi:10.1016/S0140-6736(14)61682 ...
Strano, M.; Colosimo, B.M. (30 April 2006). "Logistic regression analysis for experimental determination of forming limit ... Koistinen, D. P.; Wang, N.-M. edts.: „Mechanics of Sheet Metal Forming - Material Behavior and Deformation analysis", Plenum ... Circle grid analysis International Deep Drawing Research Group (IDDRG) Marciniak, Z.; Duncan, J. L.; Hu, S. J. (2002). ...
"Logistic regression analysis for experimental determination of forming limit diagrams". International Journal of Machine Tools ... Sheet metal forming simulation and Sheet metal forming analysis). One major objective of the International Deep Drawing ... Material Behavior and Deformation analysis", Plenum Press, 1978, ISBN 0-306-40068-5. Marciniak, Z.; Duncan, J.: "The Mechanics ...
Exact logistic regression: theory and examples. Statistics in Medicine, 1995; 14:2143-2160. Weerahandi, S. 1995. Exact ... For advanced methods such as higher-way ANOVA regression analysis, and mixed models, only exact parametric methods are ... Fisher's exact test Optimal discriminant analysis Classification tree analysis Fisher, R. A. 1954 Statistical Methods for ... Statistical Method for Data Analysis. Springer-Verlag, New York. Weerahandi, S. 2004. Generalized Inference in Repeated ...
Regressions with discrete dependent variables, such as logistic regressions. ARCH and GARCH models. Vector autoregressions. ... RATS, an abbreviation of Regression Analysis of Time Series, is a statistical package for time series analysis and econometrics ... In addition, RATS can handle cross-sectional and panel data: Linear regression, including stepwise. Regressions with ... The following is a list of the major procedures in econometrics and time series analysis that can be implemented in RATS. All ...
Odds ratios should be used only in case-control studies and logistic regression analyses". BMJ. 317 (7166): 1155-6. doi:10.1136 ... Logistic regression (for binary outcomes, or counts of successes out of a number of trials) must be interpreted in odds-ratio ... In fact, the odds ratio has much wider use in statistics, since logistic regression, often associated with clinical trials, ... but is also amenable to regression modelling, typically in a Poisson regression framework. In a simple comparison between an ...
Logistic regression approaches to DIF detection involve running a separate analysis for each item. The independent variables ... Within the logistic regression approach, leveraged values and outliers are of particular concern and must be examined prior to ... From the results of the logistic regression, DIF would be indicated if individuals matched on ability have significantly ... Common procedures for assessing DIF are Mantel-Haenszel, item response theory (IRT) based methods, and logistic regression. DIF ...
Analysis of variance and regression analysis are used to test for significant interactions. Is the yield of good cookies ... Hayes, A. F.; Matthes, J. (2009). "Computational procedures for probing interactions in OLS and logistic regression: SPSS and ... Most commonly, interactions are considered in the context of regression analyses. The presence of interactions can have ... The graph depicts an education*politics interaction, from a probability-weighted logit regression analysis of survey data. ...
Imam, E., & Kushwaha, S. P. S. (2013). Habitat suitability modelling for Gaur (Bos gaurus) using multiple logistic regression, ... Gad, S. D., & Shyama, S. K. (2011). Diet composition and quality in Indian bison (Bos gaurus) based on fecal analysis. ... using multiple logistic regression, remote sensing and GIS. Hubback, T. R. (1937). The Malayan gaur or seladang. Journal of ... A practical Sanskrit dictionary with transliteration, accentuation, and etymological analysis throughout. Oxford University ...
... logistic regression analysis". Dentomaxillofacial Radiology. 40 (3): 133-140. doi:10.1259/dmfr/24726112. ISSN 0250-832X. Gruica ... a comparative clinicopathological analysis". Oral Dis. 2 (3): 228-31. doi:10.1111/j.1601-0825.1996.tb00229.x. PMID 9081764. ...
... logistic regression analysis". Dentomaxillofacial Radiology. 40 (3): 133-140. doi:10.1259/dmfr/24726112. ISSN 0250-832X. ... The definitive diagnosis is by histologic analysis, i.e. excision and examination under the microscope. Under the microscope, ...
... logistic regression is a type of regression analysis used for predicting the outcome of a categorical dependant variable (with ... at least one pair βj≠βj' in Multiple linear regression or in Logistic regression. Usually, it tests more than two parameters of ... The model that has the constant regression function fits as well as the regression model, which means that no further analysis ... like the ANOVA overall F test in Analysis of Variance or F Test in Analysis of covariance or the F Test in Linear Regression, ...
"Prognostic modelling with logistic regression analysis: a comparison of selection and estimation methods in small data sets". ... "A simulation study of the number of events per variable in logistic regression analysis". Journal of Clinical Epidemiology. 49 ... the one in ten rule is a rule of thumb for how many predictors can be derived from data when doing regression analysis (in ... "Relaxing the Rule of Ten Events per Variable in Logistic and Cox Regression". American Journal of Epidemiology. 165 (6): 710- ...
Techniques such as logistic regression and probit regression can be used for empirical analysis of discrete choice. Estimation ... This third requirement distinguishes discrete choice analysis from forms of regression analysis in which the dependent variable ... and demand can be modeled empirically using regression analysis. On the other hand, discrete choice analysis examines ... The description of the model is the same as model K, except the unobserved terms have normal distribution instead of logistic. ...
Variables that have independent predictive value in a logistic regression analysis are incorporated into the risk index. ...
Hosmer DW, Lemesbow S. Goodness of fit tests for the multiple logistic regression model, 1980, 401 cites. Iman RL, Conover WJ. ... Small sample sensitivity analysis techniques for computer models.with an application to risk assessment, 1980, 312 cites. ... Robust regression using iteratively reweighted least-squares, 1977, 526 cites. Sugiura N. Further analysts of the data by ... Helland IS, On the structure of partial least squares regression, 1988, 246 cites. McCulloch JH. Simple consistent estimators ...
doi:10.1007/s00254-005-1228-z. Ohlmacher, G (2003). "Using multiple logistic regression and GIS technology to predict landslide ... The analysis is used to identify the factors that are related to landslides, estimate the relative contribution of factors ... Chen, Zhaohua; Wang, Jinfei (2007). "Landslide hazard mapping using logistic regression model in Mackenzie Valley, Canada". ... Landslide hazard analysis and mapping can provide useful information for catastrophic loss reduction, and assist in the ...
Classification and regression tree analysis determined a split of organism MIC between 2 and 4 mg/liter and predicted ... In logistic regression controlling for confounders, each imipenem MIC doubling dilution doubled the probability of death. This ... A meta-analysis of 17 studies investigating the clinical effectiveness of fosfomycin in four multidrug-resistant strains of ... The CRE strains in the sinks and the strains infecting the ICU patients were identical per genetic analysis. At-risk patients ...
Logistic (Bernoulli) / Binomial / Poisson regressions. Partition of variance. *Analysis of variance (ANOVA, anova) ... Mosteller, Frederick (1977). Data analysis and regression : a second course in statistics. Reading, Mass: Addison-Wesley Pub. ... This ensures that subsequent user errors cannot inadvertently perform meaningless analyses (for example correlation analysis ... Cliff, N. (1996). Ordinal Methods for Behavioral Data Analysis. Mahwah, NJ: Lawrence Erlbaum. ISBN 0-8058-1333-0 ...
... regression). This algorithm can be used to predict probabilities associated with ... - Selection from Python Data Analysis [ ... Classification with logistic regression Logistic regression is a type of a classification algorithm (see http://en.wikipedia. ... Logistic regression is based on the logistic function, which has values in the range between 0 and 1-just like for ... Logistic regression is a type of a classification algorithm (see http://en.wikipedia.org/wiki/Logistic_regression). This ...
... 2008-36-0199. ... Citation: Magri, M., "Analysis of Vehicle Customer Satisfaction Data using the Binary Logistic Regression," SAE Technical Paper ... Unlike standard regression models, the binary logistic regression is appropriate for non-continuous binary responses. It ... This paper presents the binary logistic regression as an alternative to construct customer satisfaction models. A case study of ...
Perform sentiment analysis of tweets using logistic regression and then naïve Bayes, b) Use vector space models to discover ... Tweets and other types of texts often have handles and URLs, but these dont add any value for the task of sentiment analysis. ... Machine Translation, Word Embeddings, Locality-Sensitive Hashing, Sentiment Analysis, Vector Space Models ... you will have designed NLP applications that perform question-answering and sentiment analysis, created tools to translate ...
The ... - Selection from JMP 10 Basic Analysis and Graphing, Second Edition [Book] ... Chapter 7 Performing Simple Logistic Regression Using the Fit Y by X or Logistic Platform The Logistic platform fits the ... Ordinal logistic regression models the probability of being less than or equal to a given response. This has the effect of ... Nominal logistic regression estimates a set of curves to partition the probability among the responses. ...
A multivariate logistic regression analysis of risk factors for blunt cerebrovascular injury.. Berne JD1, Cook A, Rowe SA, ... Multivariate logistic regression models for BCVI, BCAI (blunt internal carotid artery injury), and BVAI (blunt vertebral artery ... Independent predictors of BCVI on multivariate logistic regression were CSI (OR = 7.46), mandible fracture (OR = 2.59), basilar ... Univariate analysis found cervical spine fracture (CSI) (RR = 10.4), basilar skull fracture (RR = 3.60), and mandible fracture ...
Understanding logistic regression analysis (LRA) is essential to making reliable predictions and also for analysing a discrete ... Outsource Logistic Regression Analysis to Outsource2india. Do you require logistic regression analysis for your business? ... by using the powerful Logistic Regression Analysis (LRA) model.. Understanding Logistics Regression Analysis (LRA). You may ... This is called Logistic Regression Analysis (LRA). The outcome of a logistic analysis is usually measured with a dichotomous ...
The SAS/STAT procedures addressed are PROC FREQ, PROC LOGISTIC, and PROC GENMOD. The ODS Statistical Graphics procedures used ... outlier detection Multinomial Logistic Regression. *ordinal logistic regression *nominal logistic regression Advanced Topics. * ... stratified contingency table analysis Binary Logistic Regression. *introduction to logistic regression *adding categorical ... use the FREQ procedure for preliminary analyses*recognize when logistic regression is appropriate *write code in the LOGISTIC ...
... on WN Network delivers the latest Videos and Editable pages for News & Events, including ... Logistic regression. In statistics, logistic regression, or logit regression, or logit model is a regression model where the ... Logistic regression. In statistics, logistic regression, or logit regression, or logit model is a regression model where the ... Latest News for: logistic regression analyses. Edit Voters ready to introduce a brave new world in 2019. *. ...
... but the art of data analysis is about choosing and using multiple tools. Instead of presenting isolated techniques, this text ... Regression Modeling Strategies. Book Subtitle. With Applications to Linear Models, Logistic Regression, and Survival Analysis. ... Regression Modeling Strategies. With Applications to Linear Models, Logistic Regression, and Survival Analysis. Authors: ... logistic regression and survival analysis, topics that form the core of much of the statistical analysis carried out in a ...
A simulation study of the number of events per variable in logistic regression analysis.. Peduzzi P1, Concato J, Kemper E, ... analyzed in logistic regression analysis. The simulations were based on data from a cardiac trial of 673 patients in which 252 ... according to a logistic model derived from the full sample. Simulation results for the regression coefficients for each ... Although other factors (such as the total number of events, or sample size) may influence the validity of the logistic model, ...
... an ordinal logistic regression, based on a main effects experimental design.The model provides several overall desirability ... In the Conjoint Analysis (COA) model proposed here - a new approach to estimate more than one response function-an extension of ... A. Luca, "Ordinal Logistic Regression for the Estimate of the Response Functions in the Conjoint Analysis," iBusiness, Vol. 3 ... Ordinal Logistic Regression for the Estimate of the Response Functions in the Conjoint Analysis () ...
Regression analysis. To get the adjusted effect of selected factors for IPM adoption, we consider a binary logistic regression ... Determination of Influencing Factors for Integrated Pest Management Adoption: A Logistic Regression Analysis. Talukder A1*, ... For details on binary logistic regression model . The software that we used for data analysis purpose is SPSS (version 20 ... A Logistic Regression Analysis. Agrotechnology 6:163. Doi: 10.4172/2168-9881.1000163 Copyright: © 2017 Talukder A, et al. This ...
... logistic regression analysis was used to find the most important factors, that influenced the outcome of an accident with a ... For the 1993-1997 Dutch national accident data, logistic regression analysis was used to find the most important factors, that ... THE NECESSARY EXTENSION OF TRADITIONAL FREQUENCY COUNTS WITH LOGISTIC REGRESSION ANALYSIS 2001-06-0014. ... It was concluded that the combination of frequency counts and logistic regression is a necessary extension to prevent the ...
... ... was tested with ordinal logistic regression analysis using the whole cohort. Results of ordered adjusted (multivariate) and ... In the ordered logistic regression, the modeling strategy was to chunkwise delete nonsignificant predictors (deletion of ... with several sociodemographic parameters was tested using ordered univariate and multivariate logistic regression analysis. ...
Logistic Regression and Linear Discriminant Analyses in Evaluating Factors Associated with Asthma Prevalence among 10- to 12- ... "Logistic Regression and Linear Discriminant Analyses in Evaluating Factors Associated with Asthma Prevalence among 10- to 12- ...
Logistic Regression and Linear Discriminant Analyses in Evaluating Factors Associated with Asthma Prevalence among 10- to 12- ... M. E. Montgomery, M. E. White, and S. W. Martin, "A comparison of discriminant analysis and logistic regression for the ... M. Pohar, M. Blas, and S. Turk, "Comparison of logistic regression and linear discriminant analysis: a simulation study," ... T. Brenn and E. Arnesen, "Selecting risk factors: a comparison of discriminant analysis, logistic regression and Coxs ...
On logistic regression analysis with each prognostic variable separately, power (Z = +3.30), tone (Z = +2.37), sensory loss (Z ... On multiple logistic regression analysis, the best model predicting six month outcome included power, paraplegia score, CMCT ... We initially undertook a univariate logistic regression analysis, and then we used the variables having significance ,0.4 for ... The best set of variables predicting outcome was obtained by stepwise multiple logistic regression analysis.13 ...
We developed the Likelihood Ratio Test (LRT) in the context of ordinary logistic regression models and logistic regression ... simulation studies were conducted to compare the power of the ordinary logistic regression models to the logistic regression ... Power analysis of the likelihood ratio test for logistic regression mixtures. en_US. ... EM algorithm, Empirical null distribution, Likelihood ratio test, Logistic regression mixture, Power analysis. en_US. ...
We developed the Likelihood Ratio Test (LRT) in the context of ordinary logistic regression models and logistic regression ... simulation studies were conducted to compare the power of the ordinary logistic regression models to the logistic regression ... The logistic regression mixture models resulted in the improvement in power to detect the association between the two variables ... ordinary logistic regression model). Essentially, the only factors that affected improvement in power were slope and mixing ...
Conditional logistic regression avoids the possibility of bias when the number of studies is very large in a GLM analysis and ... Fixed versus Mixed Parameterization in Logistic Regression Models: Application to Meta-Analysis. ... and conditional logistic regression (clogit) are compared in a meta-analysis of 43 studies assessing the effect of diet on ... We also perform simulation studies to assess distributional behavior of regression estimates and tests of fit. Other ...
Elemental analysis. of burnt human bone for classifying sex and age at death by logistic regression K. Sawasdee, M. Tiensuwan, ... Elemental analysis of burnt human bone for classifying sex and age at death by logistic regression† ... Binary and multinomial logistic regressions were required to classify sex and age group at death, respectively. Regression ... the relationship between bone chemical compositions and sex/age groups of the deceased using logistic regression analysis. ...
Regression Analysis with the Ordered Multinomial Logistic Model. Braden Hoelzle Paper presented at the annual meeting of the ... 多元 logistic 回归分析. multiple logistic regression analysis. 主要内容. logistic 回归分析的基本概念 logistic ... Logistic Regression -. outline. basic concepts of logistic regression finding logistic regression coefficients using excels ... what is regression analysis? relevance of regression analysis regression modelling process ols regression ...
... the health associations of frequent church attendance by doing a multiple logistic regression and a survival analysis that ... adjusts for other factors (Cox proportional hazards). In laymans terms, how do survival analyses and log... ... survival analysis and logistic regression By MonDie, August 11, 2014. in Applied Mathematics ... only logistic regression is a technique. It sounds to me like survival analysis simply refers to the overall aim/goal of ...
Empirical bias analysis of random effects predictions in linear and logistic mixed model regression. Posted on July 30, 2015 by ... In particular, the shrinkage of logistic regression model with 1000-2000 observations per case is almost the same at that of a ... On the other hand the second simulation examines a separate issue, namely whether the non-linearity of the logistic regression ... Predicted v.s. simulated random effects for logistic and linear mixed regression as a function of the number of observations ...
Reliability of Pharmacodynamic Analysis by Logistic Regression: Mixed-effects Modeling Wei Lu, Ph.D.; James G. Ramsay, M.D.; ... Reliability of Pharmacodynamic Analysis by Logistic Regression: Mixed-effects Modeling You will receive an email whenever this ... Reliability of Pharmacodynamic Analysis by Logistic Regression: Mixed-effects Modeling. Anesthesiology 12 2003, Vol.99, 1255- ... Wei Lu, James G. Ramsay, James M. Bailey; Reliability of Pharmacodynamic Analysis by Logistic Regression: Mixed-effects ...
PredictorsModelsDependentProbabilitiesStepwise logistic regression analysisProbabilityMultinomial logistic regressionsBinomial logistic regressionDiscriminant analysis and logistic regressionSimple Logistic RegressionMETHODSEstimateEstimationNominalConditional logistic regressionUnivariateDichotomousRelationship between the categoricalAlgorithmBinary and ordinalEstimatesContinuousCoefficientSPSSEstimatorsPredictionPredictMathematicalSurvivalAbstractSentiment AnalysisOutcomesStatistical analysis
- In statistics, we use regression analysis to predict the result of a categorical dependent variable based on one or more predictors or independent variables. (outsource2india.com)
- Then, Our regression model explored factors that were likely predictors of voting preferences. (wn.com)
- I have a non-ordinal categorical dependent variable with 3 choice outcomes and 20 ordinal categorical predictors and want to do a multinomial logistic regression. (stackexchange.com)
- However, I want to reduce the predictors to just a few variables with factor analysis. (stackexchange.com)
- Do I replace my original 20 predictors with these 5 regression factor score variables, or do the factors need to be on another format before using them as predictors? (stackexchange.com)
- Provided that the factor analysis is itself valid, then you can replace your 20 predictors with the 5 factor score variables. (stackexchange.com)
- Binary logistic regression is used to predict the odds of being a case based on the values of the independent variables (predictors). (wikipedia.org)
- What you can do, and many people do, is to use the logistic regression model to calculate predicted probabilities at specific values of a key predictor, usually when holding all other predictors constant. (theanalysisfactor.com)
- Each model has its own intercept and regression coefficients-the predictors can affect each category differently. (theanalysisfactor.com)
- By using a stepwise logistic regression analysis, we determined that the best predictors of postoperative infection were rejection and postoperative transfusion requirements. (elsevier.com)
- Unlike standard regression models, the binary logistic regression is appropriate for non-continuous binary responses. (sae.org)
- This paper presents the binary logistic regression as an alternative to construct customer satisfaction models. (sae.org)
- Ordinal logistic regression models the probability of being less than or equal to a given response. (oreilly.com)
- Multivariate logistic regression models for BCVI, BCAI (blunt internal carotid artery injury), and BVAI (blunt vertebral artery injury) were developed to explore the relative contributions of the various risk factors. (nih.gov)
- Unlike linear regression models, which are used to predict a continuous outcome variable, logistic regression models are mostly used to predict a dichotomous categorical outcome, LRAs are frequently used in business analysis applications. (outsource2india.com)
- A. De Luca and S. Ciapparelli, "Multivariate Logistic Re- gression for the Estimate of Response Functions in the Conjoint Analysis," Proceedings MTISD 2008-Methods, Models and Information Technologies for Decision Support Systems, Università del Salento, Lecce, 2008, pp. 23-24. (scirp.org)
- We developed the Likelihood Ratio Test (LRT) in the context of ordinary logistic regression models and logistic regression mixture models. (suny.edu)
- Based on this null distribution, simulation studies were conducted to compare the power of the ordinary logistic regression models to the logistic regression mixture models. (suny.edu)
- The logistic regression mixture models resulted in the improvement in power to detect the association between the two variables, compared with the ordinary logistic regression models. (suny.edu)
- Logistic regression models analyzed associations between attendance and subsequent improvements in health practices and social connections. (scienceforums.net)
- Proportional hazards models are a class of survival models [i.e. survival analysis] in statistics. (scienceforums.net)
- Note that the first question directly assesses whether the random effect estimators reflect the underlying (but unobserved) "true" value of the individual practitioner effect in logistic regression models for surgical complications. (r-bloggers.com)
- comparing logistic regression to logistic-additive models. (bactra.org)
- The other problem is that without constraining the logistic models, we can end up with the probability of choosing all possible outcome categories greater than 1. (ucla.edu)
- It's called logistic regression models_V3_complete. (lynda.com)
- I've also included another spreadsheet named logistic … regression models_V1_blank in your exercise files. (lynda.com)
- and how to present and interpret your linear and logistic regression models. (lynda.com)
- The problem then becomes one of simultaneously estimating multinomial logistic regressions with restrictions across the models. (econbiz.de)
- I'll present two regression models. (smallpict.com)
- Because logistic regression is not my strong suit, I am researching the best way to evaluate these global models. (smallpict.com)
- Linear Regression models, both simple and multiple, assess the association between independent variable(s) (Xi) - sometimes called exposure or predictor variables - and a continuous dependent variable (Y) - sometimes called the outcome or response variable. (cdc.gov)
- What is not easy is knowing which variables to include in your analyses, how to represent them, when to worry about confounding, determining if your models are any good and knowing how to interpret them. (cdc.gov)
- Logistic random effects models are a popular tool to analyze multilevel also called hierarchical data with a binary or ordinal outcome. (biomedcentral.com)
- We fitted logistic random effects regression models with the 5-point Glasgow Outcome Scale (GOS) as outcome, both dichotomized as well as ordinal, with center and/or trial as random effects, and as covariates age, motor score, pupil reactivity or trial. (biomedcentral.com)
- Three data sets (the full data set and two sub-datasets) were analysed using basically two logistic random effects models with either one random effect for the center or two random effects for center and trial. (biomedcentral.com)
- On relatively large data sets, the different software implementations of logistic random effects regression models produced similar results. (biomedcentral.com)
- The focus in this Second Edition is again on logistic regression models for individual level data, but aggregate or grouped data are also considered. (missouri.edu)
- Structural analysis uses models to simulate the market, and estimate (predict) what causes what to happen. (marketingscience.biz)
- Thus, using logistic regression, a series of models should be run. (marketingscience.biz)
- The lecture are very exciting and detailed, though little hard and too straight forward sometimes, but Youtube helped in Regression models. (coursera.org)
- In regression models, we often want a measure of the unique effect of each X on Y. If we try to express the effect of X on the likelihood of a categorical Y having a specific value through probability, the effect is not constant. (theanalysisfactor.com)
- These differences in probabilities don't line up with the p-values in logistic regression models, though. (theanalysisfactor.com)
- Logistic regression is part of a category of statistical models called generalized linear models. (sfsu.edu)
- This broad class of models includes ordinary regression and ANOVA, as well as multivariate statistics such as ANCOVA and loglinear regression. (sfsu.edu)
- The result is M-1 binary logistic regression models. (theanalysisfactor.com)
- Why not just run a series of binary regression models? (theanalysisfactor.com)
- You could, and people used to, before multinomial regression models were widely available in software. (theanalysisfactor.com)
- Logistic models are applied in many fields, such as psychology, education, sociology and finance. (scirp.org)
- The dataset is relatively small, and the authors use stepwise logistic regression models to detect small differences. (cdc.gov)
- An often overlooked problem in building statistical models is that of endogeneity, a term arising from econometric analysis, in which the value of one independent variable is dependent on the value of other predictor variables. (cdc.gov)
- Additionally, the correlation between the dependent variables can create significant multicollinearity, which violates the assumptions of standard regression models and results in inefficient estimators. (cdc.gov)
- This module explores regression models, which allow you to start with data and discover an underlying process. (coursera.org)
- Regression models are the key tools in predictive analytics, and are also used when you have to incorporate uncertainty explicitly in the underlying data. (coursera.org)
- You'll learn more about what regression models are, what they can and cannot do, and the questions regression models can answer. (coursera.org)
- In this paper, the personal credit assessment models were established by combining back-propagation neural network (BPNN) and logistic regression, to estimate the customers' behaviors for a communication corporation. (scirp.org)
- The publication ' Regression modeling strategies : with applications to linear models, logistic and ordinal regression, and survival analysis ' is placed in the Top 10000 of the best publications in CiteWeb. (citeweb.info)
- Additionally, the publicaiton ' Regression modeling strategies : with applications to linear models, logistic and ordinal regression, and survival analysis ' is placed in the Top 100 among other scientific works published in 2015. (citeweb.info)
- In Logistic Regression, the connection between the categorical dependent variable and the continuous independent variables is measured by changing the dependent variable into probability scores. (outsource2india.com)
- Logistic regression measures the relationship between the categorical dependent variable and one or more independent variables by estimating probabilities using a logistic function , which is the cumulative logistic distribution. (wn.com)
- The other practical challenge is that it is possible that the best predictor variable may end up with relatively little weight in the factor analysis, so it may be useful to only do the factor analysis with variables that are known to have some predictive relationship with your dependent variable. (stackexchange.com)
- How to handle more than one dependent variable (categorical) in logistic regression? (stackexchange.com)
- Cases where the dependent variable has more than two outcome categories may be analysed in multinomial logistic regression, or, if the multiple categories are ordered, in ordinal logistic regression. (wikipedia.org)
- The reason for using logistic regression for this problem is that the values of the dependent variable, pass and fail, while represented by "1" and "0", are not cardinal numbers. (wikipedia.org)
- Ordinal logistic regression deals with dependent variables that are ordered. (wikipedia.org)
- Multinomial logistic regression is used when the dependent variable in question is nominal (equivalently categorical, meaning that it falls into any one of a set of categories that cannot be ordered in any meaningful way) and for which there are more than two categories. (wikipedia.org)
- Multinomial logistic regression is a particular solution to the classification problem that assumes that a linear combination of the observed features and some problem-specific parameters can be used to determine the probability of each particular outcome of the dependent variable. (wikipedia.org)
- As noted, the dependent variable Y i for a Logistic Regression is dichotomous , which means that it can take on one of two possible values. (cdc.gov)
- function that you use in logistic regression is also known as the link function because it connects, or links, the values of the independent variables to the probability of occurrence of the event defined by the dependent variable. (cdc.gov)
- It is similar to ordinary regression in that there is a dependent variable that depends on one or more independent variables. (marketingscience.biz)
- The use of logistic regression in terms of market basket becomes obvious when it is understood that the predicted dependent variable is a probability. (marketingscience.biz)
- Although not as common and not discussed in this treatment, applications of logistic regression have also been extended to cases where the dependent variable is of more than two cases, known as multinomial or polytomous [Tabachnick and Fidell (1996) use the term polychotomous]. (sfsu.edu)
- In multinomial logistic regression the dependent variable is dummy coded into multiple 1/0 variables. (theanalysisfactor.com)
- Logistic regression is based on the logistic function , which has values in the range between 0 and 1-just like for probabilities. (oreilly.com)
- The logistic function can therefore be used to transform arbitrary values into probabilities. (oreilly.com)
- The Logistic platform fits the probabilities for response categories to a continuous x predictor. (oreilly.com)
- You'll also see how logistic regression will allow you to estimate probabilities of success. (coursera.org)
- Related to: Show posterior probability takes the form of the logistic function I basically want to derive the sigmoid function from conditional and total probabilities. (stackexchange.com)
- Nominal logistic regression estimates a set of curves to partition the probability among the responses. (oreilly.com)
- We are proposing to use a simple computer program based on multivariate analysis to calculate the probability of the event of surgical morbidity or mortality. (biomedcentral.com)
- The graph shows the probability of passing the exam versus the number of hours studying, with the logistic regression curve fitted to the data. (wikipedia.org)
- Simple logistic regression lets you answer questions like, "how does gender affect the probability of having hypertension? (cdc.gov)
- Multiple logistic regression lets you answer the question, "how does gender affect the probability of having hypertension, after accounting for - or unconfounded by - or independent of - age, income, etc. (cdc.gov)
- In theory, any probability distribution can be used, however the most popular choices include the normal, uniform, and the logistic distributions. (encyclopedia.com)
- Since logistic regression calculates the probability or success over the probability of failure, the results of the analysis are in the form of an odds ratio. (sfsu.edu)
- For example, logistic regression is often used in epidemiological studies where the result of the analysis is the probability of developing cancer after controlling for other associated risks. (sfsu.edu)
- M. E. Montgomery, M. E. White, and S. W. Martin, "A comparison of discriminant analysis and logistic regression for the prediction of coliform mastitis in dairy cows," Canadian Journal of Veterinary Research , vol. 51, no. 4, pp. 495-498, 1987. (hindawi.com)
- An important aim of this study was to develop new selection techniques for use in discriminant analysis and logistic regression. (sun.ac.za)
- Equivalently, in the latent variable interpretations of these two methods, the first assumes a standard logistic distribution of errors and the second a standard normal distribution of errors. (wn.com)
- George Antonogeorgos, Demosthenes B. Panagiotakos, Kostas N. Priftis, and Anastasia Tzonou, "Logistic Regression and Linear Discriminant Analyses in Evaluating Factors Associated with Asthma Prevalence among 10- to 12-Years-Old Children: Divergence and Similarity of the Two Statistical Methods," International Journal of Pediatrics , vol. 2009, Article ID 952042, 6 pages, 2009. (hindawi.com)
- Notice there is no mention of survival analysis in their section titled Methods. (scienceforums.net)
- Methods to compute factor scores, and what is the "score coefficient" matrix in PCA or factor analysis? (stackexchange.com)
- Multivariate Methods for Interstructural Analysis. (rdrr.io)
- Linear discriminant and logistic regression (LR) are the basic robust and interpretative linear methods. (scirp.org)
- The lasso, the LARS algorithm and the non-negative garrotte are recently proposed regression methods that can be used to select individual variables. (citeweb.info)
- Traditional statistic methods such as t-test, chi-square test and multi-variable logistic regression were applied to analyze baseline information. (medsci.org)
- A. Luca, "Ordinal Logistic Regression for the Estimate of the Response Functions in the Conjoint Analysis," iBusiness , Vol. 3 No. 4, 2011, pp. 383-389. (scirp.org)
- The latent variable in the multinomial logistic regression is replaced with an estimate based on responses to all other items. (econbiz.de)
- It is well known that in logistic regression, where the outcome is measured with error, a biased estimate of the association between the outcome and a risk factor may result if no proper adjustment is made. (cdc.gov)
- The Logistic platform is the nominal or ordinal by continuous personality of the Fit Y by X platform. (oreilly.com)
- Multinomial logistic regression is for modeling nominal outcome variables, in which the log odds of the outcomes are modeled as a linear combination of the predictor variables. (ucla.edu)
- Is it appropriate to use binary logistic regression when you have polytonomus nominal predictor variables eg. (theanalysisfactor.com)
- Univariate analyses exploring associations between individual risk factors and BCVI were performed using Fisher's exact test for dichotomous variables and Student's t test for continuous variables. (nih.gov)
- The association between the intensity of low back pain and sciatica with several sociodemographic parameters was tested using ordered univariate and multivariate logistic regression analysis. (healio.com)
- Univariate and multivariate logistic regression analyses were conducted to determine the relative value of each sonographic feature. (ajnr.org)
- At univariate analysis, all sonographic features assessed were found to be important. (ajnr.org)
- In this work, we investigate a sparse logistic regression with the L 1/2 penalty for gene selection in cancer classification problems, and propose a coordinate descent algorithm with a new univariate half thresholding operator to solve the L 1/2 penalized logistic regression. (biomedcentral.com)
- The outcome of a logistic analysis is usually measured with a dichotomous variable that can assume only two discrete values. (outsource2india.com)
- Logistic regression allows one to predict a discrete outcome, such as group membership, from a set of variables that may be continuous, discrete, dichotomous, or a mix of any of these. (sfsu.edu)
- Additionally, analysis of the mice's running patterns revealed that trajectories are fairly stereotyped yet modulated by the amount of sensory evidence, suggesting that the navigational component of this task may provide a continuous readout correlated to the underlying cognitive variables. (frontiersin.org)
- However, discriminant analysis can only be used with continuous independent variables. (sfsu.edu)
- Thus, in instances where the independent variables are a categorical, or a mix of continuous and categorical, logistic regression is preferred. (sfsu.edu)
- From memory, SPSS has one or two (HOMALS and Categorical Principal Components Analysis). (stackexchange.com)
- Mnogomernyj statisticheskij analiz v jekonomicheskih zadachah: komp'juternoe modelirovanie v SPSS: Uchebnoe posobie [Multidimensional Statistical Analysis of Economic Problems: Computer Modeling in the SPSS: Tutorial] , edited by I.V. Orlova. (cplire.ru)
- I can't for the life of me figure out what type of analysis I need to run in SPSS and I am EXTREMELY statistically delayed so any responses in the most simplest explanation would be amazing. (stackexchange.com)
- A logistic regression is a technique where you discover the relative weights of the various inputs to create the most accurate prediction of some kind of sorting or categorical determination. (scienceforums.net)
- The logistic regression method was used for deriving annoyance prediction curve. (koreascience.or.kr)
- Consider using logistic analysis if you would like to predict discrete outcomes. (outsource2india.com)
- This point is especially important to take into account if the analysis aims to predict how choices would change if one alternative was to disappear (for instance if one political candidate withdraws from a three candidate race). (wikipedia.org)
- Discriminant analysis is also used to predict group membership with only two groups. (sfsu.edu)
- Professor Harrell has produced a book that offers many new and imaginative insights into multiple regression, logistic regression and survival analysis, topics that form the core of much of the statistical analysis carried out in a variety of disciplines, particularly in medicine. (springer.com)
- They investigate the health associations of frequent church attendance by doing a multiple logistic regression and a survival analysis that adjusts for other factors ( Cox proportional hazards ). (scienceforums.net)
- In layman's terms, how do survival analyses and logistic regressions proceed? (scienceforums.net)
- It sounds to me like survival analysis simply refers to the overall aim/goal of looking at who lived and who died. (scienceforums.net)
- By the end of this Specialization, you will have designed NLP applications that perform question-answering and sentiment analysis, created tools to translate languages and summarize text, and even built a chatbot! (coursera.org)
- You'll also learn about the application of these ideas to problems like sentiment analysis and word translation. (coursera.org)
- For this particular example of sentiment analysis, you have two classes. (coursera.org)
- That makes this dataset a unique perspective on the popular topic of sentiment analysis. (azure.ai)
- While binomial / binary logistic regression refers mostly to two possible outcomes usually coded as "0" and "1", multinomial logistic regression refers to three or more possible outcomes, such as yes/no/maybe scenarios for purchasing products. (outsource2india.com)
- Multiple logistic regression analyses, one for each pair of outcomes: One problem with this approach is that each analysis is potentially run on a different sample. (ucla.edu)
- Statistical analysis was conducted in a discovery set of 676 cancer cases and 744 controls. (nature.com)
- You'll apply the R programming language and statistical analysis techniques to carefully explained examples based in marketing, business intelligence, and decision support. (manning.com)
- Statistical Analysis of the Influence of the Type of Pathology at the Quantitative Characteristics of Medical Images. (cplire.ru)