**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.

**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.

**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.

**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.

**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.

**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.

**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.

**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.

**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.

**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.

**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.

**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.

**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.

**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.

**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.

**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.

**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)

**Severity of Illness Index**: Levels within a diagnostic group which are established by various measurement criteria applied to the seriousness of a patient's disorder.

**Neoplasm Regression, Spontaneous**: Disappearance of a neoplasm or neoplastic state without the intervention of therapy.

**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)

**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.

**United States**

**Japan**

**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.

**Longitudinal Studies**: Studies in which variables relating to an individual or group of individuals are assessed over a period of time.

**Smoking**: Inhaling and exhaling the smoke of burning TOBACCO.

**Pregnancy**: The status during which female mammals carry their developing young (EMBRYOS or FETUSES) in utero before birth, beginning from FERTILIZATION to BIRTH.

**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.

**China**: A country spanning from central Asia to the Pacific Ocean.

**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.

**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.

**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.

**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.

**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.

**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.

**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)

**Genotype**: The genetic constitution of the individual, comprising the ALLELES present at each GENETIC LOCUS.

**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.

**Educational Status**: Educational attainment or level of education of individuals.

**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).

**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.

**Health Status**: The level of health of the individual, group, or population as subjectively assessed by the individual or by more objective measures.

**European Continental Ancestry Group**: Individuals whose ancestral origins are in the continent of Europe.

**Health Surveys**: A systematic collection of factual data pertaining to health and disease in a human population within a given geographic area.

**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.

**Epidemiologic Methods**: Research techniques that focus on study designs and data gathering methods in human and animal populations.

**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.

**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.

**Poisson Distribution**: A distribution function used to describe the occurrence of rare events or to describe the sampling distribution of isolated counts in a continuum of time or space.

**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.

**Blood Pressure**: PRESSURE of the BLOOD on the ARTERIES and other BLOOD VESSELS.

**Asian Continental Ancestry Group**: Individuals whose ancestral origins are in the southeastern and eastern areas of the Asian continent.

**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.

**Risk**: The probability that an event will occur. It encompasses a variety of measures of the probability of a generally unfavorable outcome.

**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.

**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)

**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.

**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.

**Taiwan**

**Alcohol Drinking**: Behaviors associated with the ingesting of alcoholic beverages, including social drinking.

**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.

**Anthropometry**: The technique that deals with the measurement of the size, weight, and proportions of the human or other primate body.

**Urban Population**: The inhabitants of a city or town, including metropolitan areas and suburban areas.

**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.

**Registries**: The systems and processes involved in the establishment, support, management, and operation of registers, e.g., disease registers.

**Norway**

**Body Weight**: The mass or quantity of heaviness of an individual. It is expressed by units of pounds or kilograms.

**Aging**: The gradual irreversible changes in structure and function of an organism that occur as a result of the passage of time.

**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)

**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.

**Diet**: Regular course of eating and drinking adopted by a person or animal.

**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.

**Cardiovascular Diseases**: Pathological conditions involving the CARDIOVASCULAR SYSTEM including the HEART; the BLOOD VESSELS; or the PERICARDIUM.

**Genetic Predisposition to Disease**: A latent susceptibility to disease at the genetic level, which may be activated under certain conditions.

**Polymorphism, Single Nucleotide**: A single nucleotide variation in a genetic sequence that occurs at appreciable frequency in the population.

**Stress, Psychological**: Stress wherein emotional factors predominate.

**Residence Characteristics**: Elements of residence that characterize a population. They are applicable in determining need for and utilization of health services.

**Rural Population**: The inhabitants of rural areas or of small towns classified as rural.

**Occupational Exposure**: The exposure to potentially harmful chemical, physical, or biological agents that occurs as a result of one's occupation.

**C-Reactive Protein**: A plasma protein that circulates in increased amounts during inflammation and after tissue damage.

**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.

**Regression (Psychology)**: A return to earlier, especially to infantile, patterns of thought or behavior, or stage of functioning, e.g., feelings of helplessness and dependency in a patient with a serious physical illness. (From APA, Thesaurus of Psychological Index Terms, 1994).

**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)

**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.

**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)

**Least-Squares Analysis**: A principle of estimation in which the estimates of a set of parameters in a statistical model are those quantities minimizing the sum of squared differences between the observed values of a dependent variable and the values predicted by the model.

**Brazil**

**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.

**Data Interpretation, Statistical**: Application of statistical procedures to analyze specific observed or assumed facts from a particular study.

**Breast Neoplasms**: Tumors or cancer of the human BREAST.

**Denmark**

**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.

**Germany**

**Coronary Artery Disease**: Pathological processes of CORONARY ARTERIES that may derive from a congenital abnormality, atherosclerotic, or non-atherosclerotic cause.

**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)

**Hospitalization**: The confinement of a patient in a hospital.

**Sweden**

**Recurrence**: The return of a sign, symptom, or disease after a remission.

**Probability**: The study of chance processes or the relative frequency characterizing a chance process.

**Algorithms**: A procedure consisting of a sequence of algebraic formulas and/or logical steps to calculate or determine a given task.

**Birth Weight**: The mass or quantity of heaviness of an individual at BIRTH. It is expressed by units of pounds or kilograms.

**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).

**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.

**Blood Glucose**: Glucose in blood.

**HIV Infections**: Includes the spectrum of human immunodeficiency virus infections that range from asymptomatic seropositivity, thru AIDS-related complex (ARC), to acquired immunodeficiency syndrome (AIDS).

**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.

**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.

**Renal Dialysis**: Therapy for the insufficient cleansing of the BLOOD by the kidneys based on dialysis and including hemodialysis, PERITONEAL DIALYSIS, and HEMODIAFILTRATION.

**Diabetes Mellitus**: A heterogeneous group of disorders characterized by HYPERGLYCEMIA and GLUCOSE INTOLERANCE.

**Activities of Daily Living**: The performance of the basic activities of self care, such as dressing, ambulation, or eating.

**Hospital Mortality**: A vital statistic measuring or recording the rate of death from any cause in hospitalized populations.

**Occupational Diseases**: Diseases caused by factors involved in one's employment.

**Italy**

**Employment**: The state of being engaged in an activity or service for wages or salary.

**Self Report**: Method for obtaining information through verbal responses, written or oral, from subjects.

**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.

**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.

**Neoplasm Staging**: Methods which attempt to express in replicable terms the extent of the neoplasm in the patient.

**Sex Characteristics**: Those characteristics that distinguish one SEX from the other. The primary sex characteristics are the OVARIES and TESTES and their related hormones. Secondary sex characteristics are those which are masculine or feminine but not directly related to reproduction.

**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.

**Body Composition**: The relative amounts of various components in the body, such as percentage of body fat.

**India**

**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.

**California**

**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.

**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).

**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.

**Finland**

**Tomography, X-Ray Computed**: Tomography using x-ray transmission and a computer algorithm to reconstruct the image.

**Body Height**: The distance from the sole to the crown of the head with body standing on a flat surface and fully extended.

**Income**: Revenues or receipts accruing from business enterprise, labor, or invested capital.

**Spain**: Parliamentary democracy located between France on the northeast and Portugual on the west and bordered by the Atlantic Ocean and the Mediterranean Sea.

**Myocardial Infarction**: NECROSIS of the MYOCARDIUM caused by an obstruction of the blood supply to the heart (CORONARY CIRCULATION).

**Mothers**: Female parents, human or animal.

**Creatinine**

**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.

**Exercise**: Physical activity which is usually regular and done with the intention of improving or maintaining PHYSICAL FITNESS or HEALTH. Contrast with PHYSICAL EXERTION which is concerned largely with the physiologic and metabolic response to energy expenditure.

**Length of Stay**: The period of confinement of a patient to a hospital or other health facility.

**Students**: Individuals enrolled in a school or formal educational program.

**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".

**Seasons**: Divisions of the year according to some regularly recurrent phenomena usually astronomical or climatic. (From McGraw-Hill Dictionary of Scientific and Technical Terms, 6th ed)

**Neuropsychological Tests**: Tests designed to assess neurological function associated with certain behaviors. They are used in diagnosing brain dysfunction or damage and central nervous system disorders or injury.

**Adaptation, Psychological**: A state of harmony between internal needs and external demands and the processes used in achieving this condition. (From APA Thesaurus of Psychological Index Terms, 8th ed)

**Texas**

**Cognition Disorders**: Disturbances in mental processes related to learning, thinking, reasoning, and judgment.

**Parity**: The number of offspring a female has borne. It is contrasted with GRAVIDITY, which refers to the number of pregnancies, regardless of outcome.

**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.

**Neoplasms**: New abnormal growth of tissue. Malignant neoplasms show a greater degree of anaplasia and have the properties of invasion and metastasis, compared to benign neoplasms.

**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.

**Motor Activity**: The physical activity of a human or an animal as a behavioral phenomenon.

**Urban Health**: The status of health in urban populations.

**Mortality**: All deaths reported in a given population.

**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.

**Substance-Related Disorders**: Disorders related to substance abuse.

**Self Concept**: A person's view of himself.

**Maternal Age**: The age of the mother in PREGNANCY.

**Cholesterol, HDL**: Cholesterol which is contained in or bound to high-density lipoproteins (HDL), including CHOLESTEROL ESTERS and free cholesterol.

**Family Characteristics**: Size and composition of the family.

**Disability Evaluation**: Determination of the degree of a physical, mental, or emotional handicap. The diagnosis is applied to legal qualification for benefits and income under disability insurance and to eligibility for Social Security and workmen's compensation benefits.

**Remission, Spontaneous**: A spontaneous diminution or abatement of a disease over time, without formal treatment.

**Parents**: Persons functioning as natural, adoptive, or substitute parents. The heading includes the concept of parenthood as well as preparation for becoming a parent.

**Acute Disease**: Disease having a short and relatively severe course.

**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.

**Interviews 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.

**Marital Status**: A demographic parameter indicating a person's status with respect to marriage, divorce, widowhood, singleness, etc.

**Glomerular Filtration Rate**: The volume of water filtered out of plasma through glomerular capillary walls into Bowman's capsules per unit of time. It is considered to be equivalent to INULIN clearance.

**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)

**Anxiety**: Feeling or emotion of dread, apprehension, and impending disaster but not disabling as with ANXIETY DISORDERS.

**Psychiatric Status Rating Scales**: Standardized procedures utilizing rating scales or interview schedules carried out by health personnel for evaluating the degree of mental illness.

**Waist Circumference**: The measurement around the body at the level of the ABDOMEN and just above the hip bone. The measurement is usually taken immediately after exhalation.

**Hemoglobin A, Glycosylated**: Minor hemoglobin components of human erythrocytes designated A1a, A1b, and A1c. Hemoglobin A1c is most important since its sugar moiety is glucose covalently bound to the terminal amino acid of the beta chain. Since normal glycohemoglobin concentrations exclude marked blood glucose fluctuations over the preceding three to four weeks, the concentration of glycosylated hemoglobin A is a more reliable index of the blood sugar average over a long period of time.

**Occupations**: Crafts, trades, professions, or other means of earning a living.

**Workplace**: Place or physical location of work or employment.

**Turkey**

**Cause of Death**: Factors which produce cessation of all vital bodily functions. They can be analyzed from an epidemiologic viewpoint.

**Adolescent Behavior**: Any observable response or action of an adolescent.

**Attitude to Health**: Public attitudes toward health, disease, and the medical care system.

**Canada**: The largest country in North America, comprising 10 provinces and three territories. Its capital is Ottawa.

**Patient Acceptance of Health Care**: The seeking and acceptance by patients of health service.

**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)

**Body Weights and Measures**: Measurements of the height, weight, length, area, etc., of the human and animal body or its parts.

**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.

**Biometry**: The use of statistical and mathematical methods to analyze biological observations and phenomena.

**Nutritional Status**: State of the body in relation to the consumption and utilization of nutrients.

**Lung Neoplasms**: Tumors or cancer of the LUNG.

**Lipids**: A generic term for fats and lipoids, the alcohol-ether-soluble constituents of protoplasm, which are insoluble in water. They comprise the fats, fatty oils, essential oils, waxes, phospholipids, glycolipids, sulfolipids, aminolipids, chromolipids (lipochromes), and fatty acids. (Grant & Hackh's Chemical Dictionary, 5th ed)

**Insulin Resistance**: Diminished effectiveness of INSULIN in lowering blood sugar levels: requiring the use of 200 units or more of insulin per day to prevent HYPERGLYCEMIA or KETOSIS.

**Health Care Surveys**: Statistical measures of utilization and other aspects of the provision of health care services including hospitalization and ambulatory care.

**Continental Population Groups**: Groups of individuals whose putative ancestry is from native continental populations based on similarities in physical appearance.

**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.

**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.

**Pregnancy 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.

## Surgery-related factors and local recurrence of Wilms tumor in National Wilms Tumor Study 4. (1/22207)

OBJECTIVE: To assess the prognostic factors for local recurrence in Wilms tumor. SUMMARY BACKGROUND DATA: Current therapy for Wilms tumor has evolved through four studies of the National Wilms Tumor Study Group. As adverse prognostic factors were identified, treatment of children with Wilms tumor has been tailored based on these factors. Two-year relapse-free survival of children in the fourth study (NWTS-4) exceeded 91%. Factors once of prognostic import for local recurrence may lose their significance as more effective therapeutic regimens are devised. METHODS: Children evaluated were drawn from the records of NWTS-4. A total of 2482 randomized or followed patients were identified. Local recurrence, defined as recurrence in the original tumor bed, retroperitoneum, or within the abdominal cavity or pelvis, occurred in 100 children. Using a nested case-control study design, 182 matched controls were selected. Factors were analyzed for their association with local failure. Relative risks and 95% confidence intervals were calculated, taking into account the matching. RESULTS: The largest relative risks for local recurrence were observed in patients with stage III disease, those with unfavorable histology (especially diffuse anaplasia), and those reported to have tumor spillage during surgery. Multiple regression analysis adjusting for the combined effects of histology, lymph node involvement, and age revealed that tumor spillage remained significant. The relative risk of local recurrence from spill was largest in children with stage II disease. The absence of lymph node biopsy was also associated with an increased relative risk of recurrence, which was largest in children with stage I disease. The survival of children after local recurrence is poor, with an average survival rate at 2 years after relapse of 43%. Survival was dependent on initial stage: those who received more therapy before relapse had a worse prognosis. CONCLUSIONS: This study has demonstrated that surgical rupture of the tumor must be prevented by the surgeon, because spills produce an increased risk of local relapse. Both local and diffuse spills produce this risk. Stage II children with local spill appear to require more aggressive therapy than that used in NWTS-4. The continued critical importance of lymph node sampling in conjunction with nephrectomy for Wilms tumor is also established. Absence of lymph node biopsy may result in understaging and inadequate treatment of the child and may produce an increased risk of local recurrence. (+info)## Prolonged mating in prairie voles (Microtus ochrogaster) increases likelihood of ovulation and embryo number. (2/22207)

Prairie voles are induced ovulators that mate frequently in brief bouts over a period of approximately 24 h. We examined 1) impact of mating duration on ovulation and embryo number, 2) incidence of fertilization, 3) temporal pattern of embryo development, 4) embryo progression through the reproductive tract over time, and 5) embryo development in culture. Mating was videotaped to determine first copulation, and the ovaries were examined and the reproductive tracts flushed at 6, 8, 10, 12, 16, 20, and 24 h and 2, 3, and 4 days after first copulation. The number of mature follicles and fresh corpora lutea and the number and developmental stage of embryos were quantified. One, two-, and four-cell embryos were cultured in Whitten's medium. Mature follicles were present at the earliest time examined (6 h). Thirty-eight percent of females that had been paired for < 12 h after the first copulation ovulated, whereas all females paired >/= 12 h after the first copulation ovulated. Virtually all (> 99%) oocytes recovered from females paired for >/= 12 h after first copulation were fertilized. Pairing time after first copulation and mean copulation-bout duration were significant (p < 0.05) determinants of embryo number. Embryos entered the uterine horns and implanted on Days 3 and 4, respectively, after first copulation (Day 0). Embryos cultured in vitro underwent approximately one cell division per day, a rate similar to that in vivo. We conclude that prairie voles ovulate reliably after pairing for >/= 12 h, although some females showed exceptional sensitivity not predicted by the variables quantified. Prolonged mating for longer than 12 h increased the total embryos produced. This mechanism likely has adaptive significance for increasing offspring number. (+info)## Geographic, demographic, and socioeconomic variations in the investigation and management of coronary heart disease in Scotland. (3/22207)

OBJECTIVE: To determine whether age, sex, level of deprivation, and area of residence affect the likelihood of investigation and treatment of patients with coronary heart disease. DESIGN, PATIENTS, AND INTERVENTIONS: Routine discharge data were used to identify patients admitted with acute myocardial infarction (AMI) between 1991 and 1993 inclusive. Record linkage provided the proportion undergoing angiography, percutaneous transluminal coronary angioplasty (PTCA), and coronary artery bypass grafting (CABG) over the following two years. Multiple logistic regression analysis was used to determine whether age, sex, deprivation, and area of residence were independently associated with progression to investigation and revascularisation. SETTING: Mainland Scotland 1991 to 1995 inclusive. MAIN OUTCOME MEASURES: Two year incidence of angiography, PTCA, and CABG. Results-36 838 patients were admitted with AMI. 4831 (13%) underwent angiography, 587 (2%) PTCA, and 1825 (5%) CABG. Women were significantly less likely to undergo angiography (p < 0.001) and CABG (p < 0.001) but more likely to undergo PTCA (p < 0.05). Older patients were less likely to undergo all three procedures (p < 0.001). Socioeconomic deprivation was associated with a reduced likelihood of both angiography and CABG (p < 0.001). There were significant geographic variations in all three modalities (p < 0.001). CONCLUSION: Variations in investigation and management were demonstrated by age, sex, geography, and socioeconomic deprivation. These are unlikely to be accounted for by differences in need; differences in clinical practice are, therefore, likely. (+info)## Regional patterns of myocardial sympathetic denervation in dilated cardiomyopathy: an analysis using carbon-11 hydroxyephedrine and positron emission tomography. (4/22207)

OBJECTIVE: To assess presynaptic function of cardiac autonomic innervation in patients with advanced congestive heart failure using positron emission tomography (PET) and the recently developed radiolabelled catecholamine analogue carbon-11 hydroxyephedrine (HED) as a marker for neuronal catecholamine uptake function. DESIGN AND PATIENTS: 29 patients suffering from dilated cardiomyopathy with moderate to severe heart failure were compared with eight healthy controls. Perfusion scan was followed by HED dynamic PET imaging of cardiac sympathetic innervation. The scintigraphic results were compared with markers of disease severity and the degree of sympathetic dysfunction assessed by means of heart rate variability. RESULTS: In contrast to nearly normal perfusions, mean (SD) HED retention in dilated cardiomyopathy patients was abnormal in 64 (32)% of the left ventricle. Absolute myocardial HED retention was 10.7 (1.0)%/min in controls v 6.2 (1.6)%/min in dilated cardiomyopathy patients (p < 0.001). Moreover, significant regional reduction of HED retention was demonstrated in apical and inferoapical segments. HED retention was significantly correlated with New York Heart Association functional class (r = -0.55, p = 0. 002) and ejection fraction (r = 0.63, p < 0.001), but not, however, with plasma noradrenaline concentrations as well as parameters of heart rate variability. CONCLUSIONS: In this study, using PET in combination with HED in patients with dilated cardiomyopathy, not only global reduction but also regional abnormalities of cardiac sympathetic tracer uptake were demonstrated. The degree of abnormality was positively correlated to markers of severity of heart failure. The pathogenetic mechanisms leading to the regional differences of neuronal damage as well as the prognostic significance of these findings remain to be defined. (+info)## QT dispersion in patients with chronic heart failure: beta blockers are associated with a reduction in QT dispersion. (5/22207)

OBJECTIVE: To compare QT dispersion in patients with impaired left ventricular systolic function and in matched control patients with normal left ventricular systolic function. DESIGN: A retrospective, case-control study with controls matched 4:1 for age, sex, previous myocardial infarction, and diuretic and beta blocker treatment. SETTING: A regional cardiology centre and a university teaching hospital. PATIENTS: 25 patients with impaired left ventricular systolic function and 100 patients with normal left ventricular systolic function. MAIN OUTCOME MEASURES: QT and QTc dispersion measured by three methods: the difference between maximum and minimum QT and QTc intervals, the standard deviation of QT and QTc intervals, and the "lead adjusted" QT and QTc dispersion. RESULTS: All measures of QT/QTc dispersion were closely interrelated (r values 0.86 to 0.99; all p < 0.001). All measures of QT and QTc dispersion were significantly increased in the patients with impaired left ventricular systolic function v controls (p < 0.001): 71.9 (6.5) (mean (SEM)) v 46.9 (1.7) ms for QT dispersion, and 83.6 (7.6) v 54.3 (2.1) ms(-1-2) for QTc dispersion. All six dispersion parameters were reduced in patients taking beta blockers (p < 0.05), regardless of whether left ventricular function was normal or impaired-by 9.4 (4.6) ms for QT dispersion (p < 0.05) and by 13.8 (6. 5) ms(-1-2) for QTc dispersion (p = 0.01). CONCLUSIONS: QT and QTc dispersion are increased in patients with systolic heart failure in comparison with matched controls, regardless of the method of measurement and independently of possible confounding factors. beta Blockers are associated with a reduction in both QT and QTc dispersion, raising the possibility that a reduction in dispersion of ventricular repolarisation may be an important antiarrhythmic mechanism of beta blockade. (+info)## Early death during chemotherapy in patients with small-cell lung cancer: derivation of a prognostic index for toxic death and progression. (6/22207)

Based on an increased frequency of early death (death within the first treatment cycle) in our two latest randomized trials of combination chemotherapy in small-cell lung cancer (SCLC), we wanted to identify patients at risk of early non-toxic death (ENTD) and early toxic death (ETD). Data were stored in a database and logistic regression analyses were performed to identify predictive factors for early death. During the first cycle, 118 out of 937 patients (12.6%) died. In 38 patients (4%), the cause of death was sepsis. Significant risk factors were age, performance status (PS), lactate dehydrogenase (LDH) and treatment with epipodophyllotoxins and platinum in the first cycle (EP). Risk factors for ENTD were age, PS and LDH. Extensive stage had a hazard ratio of 1.9 (P = 0.07). Risk factors for ETD were EP, PS and LDH, whereas age and stage were not. For EP, the hazard ratio was as high as 6.7 (P = 0.0001). We introduced a simple prognostic algorithm including performance status, LDH and age. Using a prognostic algorithm to exclude poor-risk patients from trials, we could minimize early death, improve long-term survival and increase the survival differences between different regimens. We suggest that other groups evaluate our algorithm and exclude poor prognosis patients from trials of dose intensification. (+info)## Microvascular function relates to insulin sensitivity and blood pressure in normal subjects. (7/22207)

BACKGROUND: A strong but presently unexplained inverse association between blood pressure and insulin sensitivity has been reported. Microvascular vasodilator capacity may be a common antecedent linking insulin sensitivity to blood pressure. To test this hypothesis, we studied 18 normotensive and glucose-tolerant subjects showing a wide range in insulin sensitivity as assessed with the hyperinsulinemic, euglycemic clamp technique. METHODS AND RESULTS: Blood pressure was measured by 24-hour ambulatory blood pressure monitoring. Videomicroscopy was used to measure skin capillary density and capillary recruitment after arterial occlusion. Skin blood flow responses after iontophoresis of acetylcholine and sodium nitroprusside were evaluated by laser Doppler flowmetry. Insulin sensitivity correlated with 24-hour systolic blood pressure (24-hour SBP; r=-0.50, P<0.05). Capillary recruitment and acetylcholine-mediated vasodilatation were strongly and positively related to insulin sensitivity (r=0.84, P<0.001; r=0.78, P<0.001, respectively), and capillary recruitment was inversely related to 24-hour SBP (r=-0.53, P<0.05). Waist-to-hip ratio showed strong associations with insulin sensitivity, blood pressure, and the measures of microvascular function but did not confound the associations between these variables. Subsequent regression analysis showed that the association between insulin sensitivity and blood pressure was not independent of the estimates of microvascular function, and part of the variation in both blood pressure (R2=38%) and insulin sensitivity (R2=71%) could be explained by microvascular function. CONCLUSIONS: Insulin sensitivity and blood pressure are associated well within the physiological range. Microvascular function strongly relates to both, consistent with a central role in linking these variables. (+info)## Modeling breathing-zone concentrations of airborne contaminants generated during compressed air spray painting. (8/22207)

This paper presents a mathematical model to predict breathing-zone concentrations of airborne contaminants generated during compressed air spray painting in cross-flow ventilated booths. The model focuses on characterizing the generation and transport of overspray mist. It extends previous work on conventional spray guns to include exposures generated by HVLP guns. Dimensional analysis and scale model wind-tunnel studies are employed using non-volatile oils, instead of paint, to produce empirical equations for estimating exposure to total mass. Results indicate that a dimensionless breathing zone concentration is a nonlinear function of the ratio of momentum flux of air from the spray gun to the momentum flux of air passing through the projected area of the worker's body. The orientation of the spraying operation within the booth is also very significant. The exposure model requires an estimate of the contaminant generation rate, which is approximated by a simple impactor model. The results represent an initial step in the construction of more realistic models capable of predicting exposure as a mathematical function of the governing parameters. (+info)###### Simple Regression Analysis in Public Health | Coursera

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VarianceCoefficientPredictorsNonlinear regression analysisModelDataModelsMethodsMultivariateInterpretExamplesMultipleDependent variableQuantileOrdinal regressionParametersApplication of regressionResultsEstimateEstimationNonlinear RegressionMultinomial logistic regressionDataModelsGeographically Weighted RegressionVarianceLeast squaresEconometricsDependentPurpose of regressionVariablesSimple and multiple linear regTypes of regression analysisCorrelation and regression analysisMeta-regression analysisBinaryCurveCommonlyParametricSupport vector regressionLinear Regression ChannelStatistical analysesQuantile regressionSemiparametric regressionPerform a regressionMultivariate StatisticsSeemingly unrelatedApplications of regressionPredict

###### Variance1

- Generalized linear models (GLMs) calculates nonlinear regression when the variance in sample data is not constant or when errors are not normally distributed. (data-flair.training)

###### Coefficient3

- Here β is a regression coefficient. (data-flair.training)
- When we regress the dependent variable on the independent one(s) using a regression equation, we obtain a Regression Coefficient which is a measure of the degree of linear association between the cause and the effect. (bi-analytics.org)
- While R-square is simply the square of the regression coefficient giving us an idea of the goodness of fit, Adjusted R-square also compensates for the number of predictors used in order to avoid overestimation of the strength of association. (bi-analytics.org)

###### Predictors2

- Module three focuses on Cox regression with different predictors. (coursera.org)
- Based on the transformation selected in Part 1, build a multiple linear regression model with all eight predictors. (coursetutor.us)

###### Nonlinear regression analysis2

- Blog Home » R Tutorials » R Nonlinear Regression Analysis - All-inclusive Tutorial for Newbies! (data-flair.training)
- The nonlinear regression analysis in R is the process of building a nonlinear function. (data-flair.training)

###### Model9

- The Multiple Regression Analysis and Forecasting model provides a solid basis for identifying value drivers and forecasting data for input to valuation and analytical models. (business-spreadsheets.com)
- In this book, resampling application for variable selection on the basis of optimum choice of stopping rules for each data set and model simplification in various regression models are addressed. (morebooks.de)
- Our selection method first choosing appropriate cutoff values/stopping criterion's and results in selecting a good subset regression model. (morebooks.de)
- We focus on optimizing cutoff values or stopping criterion's in automated model selection methods in regression analysis due to the interest in holding only authentic predictor variables in the regression models. (morebooks.de)
- We first focus on linear regression model, and then extended our approach to generalized regression, cox regression and finally robust regression. (morebooks.de)
- There are a variety of regression methodologies that you choose based on the type of response variable, the type of model that is required to provide an adequate fit to the data, and the estimation method. (statisticsbyjim.com)
- We will also explore the transformation of nonlinear model into linear model, generalized additive models, self-starting functions and lastly, applications of logistic regression. (data-flair.training)
- This was motivated by two observations: (1) Regression modeling applications often involve complex diverse predictor-response relationships, which occur when the optimal regression models (of given regression model type) fitting two or more distinct logical groups of data are highly different. (wright.edu)
- 2) State-of-the-art regression methods are often unable to adequately model such relationships. (wright.edu)

###### Data12

- Regression analysis can be very helpful for analyzing large amounts of data and making forecasts and predictions. (wikihow.com)
- If your version of Excel displays the ribbon , go to Data , find the Analysis section, hit Data Analysis , and choose Regression from the list of tools. (wikihow.com)
- Data Analysis and choose Regression from the list of tools. (wikihow.com)
- A Panel Data Analysis Using School Reforms for Identification. (uni-muenchen.de)
- We propose a general approach of resampling techniques in regression analysis that allows us to 'choose' the stopping criterion's for each data set. (morebooks.de)
- The emphasis continues to be on exploratory data analysis rather than statistical theory. (statisticsviews.com)
- Regression analysis enables to predict easily based on given data. (gi.de)
- Count data is expressed as proportions (e.g. logistic regressions). (data-flair.training)
- I hope that in the future, if I'm successful in communicating with people about this, that there'll be a kind of upfront warning in New York Times articles: These data are based on multiple regression analysis. (edge.org)
- When dealing with real-life data, we resort to Regression Analysis for estimating the relationships among the various variables. (bi-analytics.org)
- Now, we first perform some exploratory data analysis (graphical analysis) to visually project our data. (bi-analytics.org)
- The summary function gives the 5-point summary of the residuals (estimation error values) as well as the slope and intercept of the best fit regression line that models the data. (bi-analytics.org)

###### Models7

- The purpose of this assignment is to apply multiple regression concepts, interpret multiple regression analysis models, and justify business predictions based upon the analysis. (coursetutor.us)
- Logistic Regression Models are generally used in cases when the rate of growth does not remain constant over a period of time. (data-flair.training)
- This paper first introduces pattern aided regression (PXR) models, a new type of regression models designed to represent accurate and interpretable prediction models. (wright.edu)
- This paper defines PXR models using several patterns and local regression models, which respectively serve as logical and behavioral characterizations of distinct predictor-response relationships. (wright.edu)
- The paper also introduces a contrast pattern aided regression (CPXR) method, to build accurate PXR models. (wright.edu)
- In experiments, the PXR models built by CPXR are very accurate in general, often outperforming state-of-the-art regression methods by big margins. (wright.edu)
- in fact, their complexity is just a bit higher than that of (piecewise) linear regression models and is significantly lower than that of traditional ensemble based regression models. (wright.edu)

###### Methods2

- In the literature, many variable selection methods for regression modeling have been developed whose performance depends critically on the stopping rules. (morebooks.de)
- Methods of regression analysis are clearly demonstrated, and examples containing the types of irregularities commonly encountered in the real world are provided. (statisticsviews.com)

###### Multivariate2

- We will study about logistic regression with its types and multivariate logit() function in detail. (data-flair.training)
- Multivariate logistic regression is commonly used in the fields of medical and social science. (data-flair.training)

###### Interpret1

- How does one interpret lack-of-fit issues with a Logistic Regression? (physicsforums.com)

###### Examples1

- an excellent source of examples for regression analysis. (statisticsviews.com)

###### Multiple2

- If you need 100% original papers for MIS 660 Topic 8 Multiple Regression Analysis GCU, then contact us through call or live chat. (coursetutor.us)
- A huge range of science projects are done with these multiple regression things. (edge.org)

###### Dependent variable1

- On the other hand we can say that, Regression analysis is the statistical technique that identifies the relationship between two or more quantitative variables: a dependent variable, whose value is to be predicted, and an independent or explanatory variable (or variables), about which knowledge is available. (assignmentpoint.com)

###### Quantile4

- This study investigates the factors that may influence the obesity in Turkey which is a developing country by implementing Quantile Regression (QR) methodology. (uni-muenchen.de)
- European Evidence Using Quantile Regression. (uni-muenchen.de)
- Costa-Font, J., D. Fabbri, and J. Gil (2009) "Decomposing Body Mass Index Gaps between Mediterranean Countries: A Counterfactual Quantile Regression Analysis. (uni-muenchen.de)
- Koenker, R., and K. Hallock (2001) "Quantile Regression: An Introduction," Journal of Economic Perspectives 15 (4): 43-56. (uni-muenchen.de)

###### Ordinal regression1

- Lack of Fit in Ordinal Regression -- Analysis/Alternatives? (physicsforums.com)

###### Parameters1

- Regression is nonlinear when at least one of its parameters appears nonlinearly. (data-flair.training)

###### Application of regression1

- Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgment. (statisticsviews.com)

###### Results3

- While it utilizes a range of commonly employed statistical measures to test the validity of the analysis, results are summarized in layman's terms for ease of use. (business-spreadsheets.com)
- QR regression results provide robust evidence that additional years of schooling has negative effect on individual's BMI and this effect significantly raises across different quantiles of BMI. (uni-muenchen.de)
- Chou, S. Y., M. Grossman, and H. Saffer (2002) "An Economic Analysis of Adult Obesity: Results from the Behavioral Risk Factor Surveillance System. (uni-muenchen.de)

###### Estimate1

- Regression is a statistical tool to estimate or predict the unknown values of one variable from known values of another variable. (assignmentpoint.com)

###### Estimation10

- the same explanatory variables appear in the log-log equations, which is in fact OLS is equivalent to seemingly unrelated regression, it is not possible to improve the separate least-square estimation using a seemingly unrelated regression technique. (bartleby.com)
- Demand Estimation by Regression Method - Some Statistical Concepts for application ( All the formulae marked in red for remembering. (bartleby.com)
- Further, the book considers decompositions of tensor products into natural subspaces, and addresses maximum likelihood estimation, residual analysis, influential observation analysis and testing hypotheses, where properties of estimators such as moments, asymptotic distributions or approximations of distributions are also studied. (springer.com)
- Quantile regression for robust bank efficiency score estimation ," European Journal of Operational Research , Elsevier, vol. 200(2), pages 568-581, January. (repec.org)
- In a narrower sense, regression may refer specifically to the estimation of continuous response (dependent) variables, as opposed to the discrete response variables used in classification. (wikipedia.org)
- We will begin with a review of basic statistical concepts and then go on to cover correlation, the development of the regression model, parameter estimation, statistical inference, and potential problems that can arise with regression analysis, applications, and interpretation. (umich.edu)
- and how should it inform the specification and estimation of regression models? (umich.edu)
- The literature offers two distinct reasons for incorporating sample weights into the estimation of linear regression coefficients from a model-based point of view. (rti.org)
- C. Cai , G. Wang , Y. Wen , J. Pei , X. Zhu and W. Zhuang , Superconducting transition temperature t c estimation for superconductors of the doped mgb2 system using topological index via support vector regression, Journal of Superconductivity and Novel Magnetism , 23 (2010), 745-748. (aimsciences.org)
- While separate estimation of individual generalized quantile regressions usually suffers from large variability due to lack of suffcient data, by borrowing strength across data sets, our joint estimation approach signifcantly improves the estimation effciency, which is demonstrated in a simulation study. (hu-berlin.de)

###### Nonlinear Regression8

- The article reviews the book "Nonlinear Regression," by G.A.F. Seber and C.J. Wild. (ebscohost.com)
- If the dependent variables are modeled as a non-linear function because the data relationships do not follow a straight line, use nonlinear regression instead. (ablebits.com)
- Yang, N. , Zhang, D. and Tian, Y. (2015) The Validity Analysis of Regression: Combining Uniform Experiment Design with Nonlinear Regression. (scirp.org)
- NLREG is a powerful statistical analysis program that performs linear and nonlinear regression analysis, surface and curve fitting. (nlreg.com)
- Unlike many "nonlinear" regression programs that can only handle a limited set of function forms, NLREG can handle essentially any function whose form you can specify algebraically. (nlreg.com)
- NLREG performs true nonlinear regression analysis and curve fitting, it does not transform the function into a linear form. (nlreg.com)
- In addition to performing classic nonlinear regression, NLREG can be used to find the root or minimum value of a general multivariate, nonlinear function. (nlreg.com)
- The author of NLREG is available for consulting on data modeling and nonlinear regression projects. (nlreg.com)

###### Multinomial logistic regression1

- 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)

###### Data60

- Multivariate data analysis (7th ed. (springer.com)
- Analysis of panel data (3rd ed. (springer.com)
- However, co-expression analysis using human cancer transcriptomic data is confounded by somatic copy number alterations (SCNA), which produce co-expression signatures based on physical proximity rather than biological function. (nature.com)
- The results from analyses of TCGA, CCLE, and NCI60 data sets show that GRACE can improve our understanding of how a transcriptional network is re-wired in cancer. (nature.com)
- However, no method exists to remove the confounding effect of CNAs in the analysis of gene-gene co-expression using cancer transcriptome data. (nature.com)
- Through comprehensive analyses of genetics, genomics, proteomics, metabolomics, and drug response data from the public domain, we show that GRACE can improve our understanding of how a transcriptional network is re-wired in cancer. (nature.com)
- As a formal matter, conventional regression analysis does nothing more than produce from a data set a collection of conditional means and conditional variances. (sagepub.com)
- Regression is most useful for data reduction, leading to relatively simple but rich and precise descriptions of patterns in a data set. (sagepub.com)
- The least-squares regression equation computed from their data is [pic]. (bartleby.com)
- This example shows how to prepare exogenous data for several seemingly unrelated regression (SUR) analyses. (mathworks.com)
- Using data from the National longitudinal study of youth, we ﬁnd the following results for a regression of log weekly wage on years of education, experience, experience squared and an intercept: log(earnings)i = 4.016 + 0.092 · educi + 0.079 · experi − 0.002 · exper2 i (0.222) (0.008) (0.025) (0.001) a. (5 points) Construct a 95% conﬁdence interval for the eﬀect of years of education on log weekly earnings. (scribd.com)
- Throughout the text, examples and several analyzed data sets illustrate the different approaches, and fresh insights into classical multivariate analysis are provided. (springer.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. (sagepub.com)
- Since the true form of the data-generating process is generally not known, regression analysis often depends to some extent on making assumptions about this process. (wikipedia.org)
- Regression analysis can be very helpful for analyzing large amounts of data and making forecasts and predictions. (wikihow.com)
- If your version of Excel displays the ribbon , go to Data , find the Analysis section, hit Data Analysis , and choose Regression from the list of tools. (wikihow.com)
- Data Analysis and choose Regression from the list of tools. (wikihow.com)
- Magri, M., "Analysis of Vehicle Customer Satisfaction Data using the Binary Logistic Regression," SAE Technical Paper 2008-36-0199, 2008, https://doi.org/10.4271/2008-36-0199 . (sae.org)
- 1- Prepare a paper examining a regression analysis on your collected data. (brainmass.com)
- Applied Survival Analysis, Second Edition provides a comprehensive and up-to-date introduction to regression modeling for time-to-event data in medical, epidemiological, biostatistical, and other health-related research. (ecampus.com)
- The first thing is that the regression tries to fit the existing data and the sample is not representative of the population, then the regression won't be useful just like estimating a distribution mean from a sample that is skewed massively to the left or right won't represent the true underlying mean of the population. (physicsforums.com)
- Software emphasis will be given to GeoDa and R for exploratory spatial data analysis and modeling. (umich.edu)
- Meta-analysis, a statistical method of pooling data from studies included in a systematic review, is often compromised by heterogeneity of its results. (nih.gov)
- It outlines theoretical principals underlying the techniques utilized in regression analysis and illustrates their application on a variety of data sets. (routledge.com)
- Data analysis and regression : a second course in statistics. (worldcat.org)
- I thought you might be interested in this item at http://www.worldcat.org/oclc/693419875 Title: Data analysis and regression : a second course in statistics. (worldcat.org)
- Add tags for "Data analysis and regression : a second course in statistics. (worldcat.org)
- To equip students with the necessary skills and knowledge to allow analysis of data with an awareness of effect modification and confounding. (york.ac.uk)
- By means of lectures and hands-on analysis of data from real healthrelated studies, using the statistical software package STATA the student is guided through the full range of standard statistical parametric and non-parametric techniques, ranging from frequency tables to Cox's regression. (york.ac.uk)
- Reviews the book "Regression Analysis of Count Data," by A. Colin Cameron and Pravin K. Trivedi. (ebscohost.com)
- The chapter uses the Advertising data set available from the book's website: Testing the assumptions of linear regression. (pearltrees.com)
- At the end of this module, you'll be able to determine what kinds of predictions you can make to create future strategies, understand the most powerful techniques for predictive models including regression analysis, and be prepared to take full advantage of analytics to create effective data-driven business decisions. (coursera.org)
- As this is a methodology I simply have to state how I will feed the data into regression analysis as opposed to enacting it. (mathhelpforum.com)
- Be able to describe data and carry out linear and logistic regression and non-parametric statistics. (york.ac.uk)
- Analyses throughout the text are performed using Stata Version 9, and an accompanying FTP site contains the data sets used in the book. (worldcat.org)
- This book fills this gap, providing a comprehensive, self-contained introduction to regression modeling used in the analysis of time-to-event data in epidemiological, biostatistical, and other health-related research. (worldcat.org)
- Standard least squares regressions were performed on the data to relate particular ship characteristics to deadweight. (bitre.gov.au)
- This will add the Data Analysis tools to the Data tab of your Excel ribbon. (ablebits.com)
- Relevant Skills and Experience I know statistic and data analysis very well. (freelancer.com)
- Learn from data science expert Michael Grogan in this tutorial that teaches you how to use regression analysis and R to uncover high-value business insights hidden inside large datasets. (safaribooksonline.com)
- Based on the investigation data of social position of national women in the third phase by National Women's Federation and National Bureau of Statistics in 2010, regression analysis on sex wage difference is conducted. (umn.edu)
- Many texts are excellent sources of knowledge about individual statistical tools, but the art of data analysis is about choosing and using multiple tools. (springer.com)
- Data analysis, particularly users of S-PLUS, with experience in the application of these tools will benefit the most from this book. (springer.com)
- Statistical techniques such as regression analysis are tools of action that enable accountants to make financial data meaningful to their clients. (thefreedictionary.com)
- Chen, Y. , Ma, J. and Wang, S. (2020) Spatial Regression Analysis of Pedestrian Crashes Based on Point-of-Interest Data. (scirp.org)
- Journal of Data Analysis and Information Processing , 8 , 1-19. (scirp.org)
- Many studies have conducted the safety analysis of pedestrian crashes based on zone-level data and examined a lot of related features. (scirp.org)
- It has been shown that spatial autocorrelation and spatial heterogeneity in crash data are two critical properties when developing statistical models for macro-level safety analysis. (scirp.org)
- The reproducibility of using R language to perform spatial data analysis is unparalleled, which includes plenty of spatial packages for different purposes. (scirp.org)
- Although POI data may not include traditional information used in traffic accident analysis, they can represent specific land use factors with precise locations, which are expected to be highly related to pedestrian crashes in both macro- and micro-level aspects. (scirp.org)
- By performing a regression analysis on this survey data, we can determine whether or not these variables have impacted overall attendee satisfaction, and if so, to what extent. (surveygizmo.com)
- In this paper, the principle and method of distinguish the training data and testing data were described to make a reasonable regression when uniform experiment design combined with support vector regression (SVR). (scirp.org)
- Computational Statistics & Data Analysis, 54, 219-232. (scirp.org)
- We develop a functional data analysis approach to jointly estimate a family of generalized quantile regressions. (hu-berlin.de)
- In linear regression we find the "best" line through the data. (fruition.net)
- an interesting application of this is " circular regression " where a circle is fitted to a set of data points. (nlreg.com)
- To avoid making wrong inferences, regression toward the mean must be considered when designing scientific experiments and interpreting data. (scribd.com)
- Sir Francis Galton first observed the phenomenon in the context of simple linear regression of data points. (scribd.com)
- Simply put, Data Analysis Using Regression and Multilevel/Hierarchical Models is the best place to learn how to do serious empirical research. (columbia.edu)
- Data Analysis Using Regression and Multilevel/Hierarchical Models is destined to be a classic! (columbia.edu)

###### Models37

- Misleading heuristics and moderated multiple regression models. (springer.com)
- The price sensitivity of selective demand: A meta-analysis of econometric models of sales. (springer.com)
- In regression models, the parameter vector β is estimable. (springer.com)
- There are many different linear regression models built-in in Scikit-learn, Ordinary Least Squares ( OLS ) and Least Absolute Shrinkage and Selection Operator ( LASSO ) to name two. (oreilly.com)
- 6 3.2 The Regression Specification Error Test 8 3.3 Non-linear models 9 3.4 Autocorrelation. (bartleby.com)
- Students in both the natural and social sciences often seek regression models to explain the frequency of events, such as visits to a doctor, auto accidents or job hiring. (cambridge.org)
- In order to analyze the bilinear regression models in an interpretable way, concepts from linear models are extended and applied to tensor spaces. (springer.com)
- Reciprocal Trade Agreements in Gravity Models: A Meta-Analysis ," Review of International Economics , Wiley Blackwell, vol. 18(1), pages 63-80, February. (repec.org)
- Reciprocal Trade Agreements in Gravity Models: A Meta-analysis ," Working Papers 18877, TRADEAG - Agricultural Trade Agreements. (repec.org)
- Reciprocal trade agreements in gravity models: a meta-analysis ," Economics & Statistics Discussion Papers esdp07035, University of Molise, Dept. EGSeI. (repec.org)
- We refer to both, the well-known UTAGMS method, which builds the set of general additive value functions compatible with DM's preferences, and newly introduced in this paper PROMETHEEGKS, which constructs the set of compatible outranking models via robust ordinal regression. (repec.org)
- Updated coverage of unordered and ordered polytomous logistic regression models. (sagepub.com)
- Linear Regression Models using Matrix Notation. (birzeit.edu)
- Multiple Regression Models. (birzeit.edu)
- Polynomial Regression Models. (birzeit.edu)
- Logistic Regression Models. (birzeit.edu)
- This workshop will provide an introduction to bivariate and multiple regression models. (umich.edu)
- Regression Analysis models are used to help us predict the value of one unknown variable, through one or more other variables whose values can be predetermined. (12manage.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)
- Note that R 2 s of two different models are comparable only if the dependent variables and the number of observations are the same, because R 2 measures the fraction of the total variation in the dependent variable explained by the regression equation. (encyclopedia.com)
- Specific modeling techniques include: indices of spatial autocorrelation (Moran's I, Geary's C, LISA), spatial regression models (SAR and SEM), geographically weighted regression (GWR), and conditional autoregressive models (CAR). (umich.edu)
- 1.2 Uses of Regression Models. (wiley.com)
- Correctly construct multivariate linear, logistic and Poisson regression models and to undertake survival analysis and Cox-regression modelling. (york.ac.uk)
- Applied regression analysis and generalized linear models. (york.ac.uk)
- Introduction All models are wrong, but some are useful - George Box Regression analysis marks the first step in predictive modeling. (pearltrees.com)
- This course develops the foundations of ordinary least squares (OLS) regression analysis and teaches students how to specify, estimate, and interpret multivariate regression models. (du.edu)
- VGG-16 or ResNet-50) adequately tuned can yield results close to the state-of-the-art without having to resort to more complex and ad-hoc regression models. (inria.fr)
- 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)
- This Paper presents the results of statistical analyses of ship characteristics which have been undertaken to provide input to models of ship costs and operations in particular trades. (bitre.gov.au)
- Simple linear regression models the relationship between a dependent variable and one independent variables using a linear function. (ablebits.com)
- Hi, I am familiar with similar analysis and with different regression models using SPSS. (freelancer.com)
- Spatial regression models were developed at Traffic Analysis Zone (TAZ) level using 10,333 pedestrian crash records within the Fifth Ring of Beijing in 2015. (scirp.org)
- Geographic information system (GIS) is powerful platform supporting lots of spatial regression models. (scirp.org)
- Correlation analysis refers to the measurement of association between or among variables, and regression analysis focuses primarily on the use of linear models to predict changes in the value taken by one variable in terms of changes in the values of a set of explanatory variables. (abebooks.com)
- Containing practical as well as methodological insights into both Bayesian and traditional approaches, Applied Regression and Multilevel/Hierarchical Models provides useful guidance into the process of building and evaluating models. (columbia.edu)
- For the social scientist and other applied statisticians interested in linear and logistic regression, causal inference and hierarchical models, it should prove invaluable either as a classroom text or as an addition to the research bookshelf. (columbia.edu)

###### Geographically Weighted Regression2

- These tools include Ordinary Least Squares (OLS) Regression and Geographically Weighted Regression (GWR). (esri.com)
- Geographically Weighted Regression (GWR) is one of several spatial regression techniques, increasingly used in geography and other disciplines. (esri.com)

###### Variance1

- This article presents a review of the book "Multiple Regression and Analysis of Variance," by George O. Wesolowsky. (ebscohost.com)

###### Least squares6

- Regression with qualitative and quantitative variables: An alternating least squares method with optimal scaling features ," Psychometrika , Springer;The Psychometric Society, vol. 41(4), pages 505-529, December. (repec.org)
- The earliest form of regression was the method of least squares, which was published by Legendre in 1805, and by Gauss in 1809. (wikipedia.org)
- The linear regression line is sometimes called the least squares line. (brainmass.com)
- What is the connection between 'least squares' and linear regression? (brainmass.com)
- Could 'least squares' and regression be generalized to more complicated cases than lines? (brainmass.com)
- C. Wang and D. X. Zhou , Optimal learning rates for least squares regularized regression with unbounded sampling, Journal of Complexity , 27 (2011), 55-67. (aimsciences.org)

###### Econometrics1

- My course work in undergraduate included probability / statistics courses as well as courses in econometrics ( regression analysis ). (wyzant.com)

###### Dependent17

- The equation for the i^th observation might be: There are many cases where the dependent variable is restricted to take on a limited range of values, for example only values 0 or 1 (binary logistic regression). (bartleby.com)
- More specifically, regression analysis helps one understand how the typical value of the dependent variable (or 'criterion variable') changes when any one of the independent variables is varied, while the other independent variables are held fixed. (wikipedia.org)
- Most commonly, regression analysis estimates the conditional expectation of the dependent variable given the independent variables - that is, the average value of the dependent variable when the independent variables are fixed. (wikipedia.org)
- A related but distinct approach is necessary condition analysis (NCA), which estimates the maximum (rather than average) value of the dependent variable for a given value of the independent variable (ceiling line rather than central line) in order to identify what value of the independent variable is necessary but not sufficient for a given value of the dependent variable. (wikipedia.org)
- Regression analysis is also used to understand which among the independent variables are related to the dependent variable, and to explore the forms of these relationships. (wikipedia.org)
- In restricted circumstances, regression analysis can be used to infer causal relationships between the independent and dependent variables. (wikipedia.org)
- The case of a continuous dependent variable may be more specifically referred to as metric regression to distinguish it from related problems. (wikipedia.org)
- regression analysis in which the dependent variable is assumed to be linearly related to the independent variable or variables. (dictionary.com)
- The multiple regression analysis would then identify the relationship between the dependent variable and the explanatory variables. (12manage.com)
- Regression analysis is the statistical methodology of estimating a relationship between a single dependent variable ( Y ) and a set of predictor (explanatory/independent) variables ( X 2 , X 3 , … X k ) based on a theoretical or empirical concept. (encyclopedia.com)
- 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)
- Regression analysis helps you understand how the dependent variable changes when one of the independent variables varies and allows to mathematically determine which of those variables really has an impact. (ablebits.com)
- It is a term yielded by regression analysis that indicates the sensitivity of the dependent variable to a particular independent variable . (dailystocks.com)
- While there are many types of regression analysis, at their core they all examine the influence of one or more independent variables on a dependent variable. (surveygizmo.com)
- In order to conduct a regression analysis, you'll need to define a dependent variable that you hypothesize is being influenced by one or several independent variables. (surveygizmo.com)
- The regression line represents the relationship between your independent variable and your dependent variable. (surveygizmo.com)
- First, linear regression assumes that the dependent variable (in this case site rank) is measured on an interval scale. (fruition.net)

###### Purpose of regression1

- This technique will not only classify the original test cases but will also generate new test cases required for the purpose of regression testing. (igi-global.com)

###### Variables14

- Table 1 gives some details on the variables employed in the analysis. (bartleby.com)
- REGRESSION ANALYSIS Correlation only indicates the degree and direction of relationship between two variables. (bartleby.com)
- columns since, in this example, all exogenous variables are in the regression component of each response series. (mathworks.com)
- Correlation analyses and their associated graphics depicted above, test the strength of the relationship between two variables. (esri.com)
- In statistical modeling, regression analysis is a set of statistical processes for estimating the relationships among variables. (wikipedia.org)
- In all cases, a function of the independent variables called the regression function is to be estimated. (wikipedia.org)
- Regression is a powerful, although often abused, method for assessing the relationship between two variables (simple linear regression). (isixsigma.com)
- If you use two or more explanatory variables to predict the independent variable, you deal with multiple linear regression . (ablebits.com)
- Multivariate regression takes into account several predictive variables simultaneously, thus modeling the property of interest with more accuracy. (camo.com)
- It is shown that when missing responses are imputed using the semiparametric regression method the empirical log-likelihood is asymptotically a scaled chi-square variable or a weighted sum of chi-square variables with unknown weights in the absence of auxiliary information or in the presence of auxiliary information. (hu-berlin.de)
- Regression analysis is a powerful statistical method that allows you to examine the relationship between two or more variables of interest. (surveygizmo.com)
- Regression analysis is a reliable method of identifying which variables have impact on a topic of interest. (surveygizmo.com)
- Multiple Linear Regressions allows us to add more predictor variables. (fruition.net)
- Second, linear regression assumes a straight line relationship, where in reality some variables are good, up to a point and then they are bad, the line would be curved. (fruition.net)

###### Simple and multiple linear reg1

- In statistics, they differentiate between a simple and multiple linear regression. (ablebits.com)

###### Types of regression analysis2

- While there are other types of regression analysis, teaching regression is not the objective here. (isixsigma.com)
- The results of the three types of regression analysis of the measurements in the table above are shown below. (libreoffice.org)

###### Correlation and regression analysis3

- What are some examples of practical applications for correlation and regression analysis that might be of use to us? (brainmass.com)
- In Correlation and Regression Analysis: A Historian's Guide Thomas J. Archdeacon provides historians with a practical introduction to the use of correlation and regression analysis. (abebooks.com)
- Correlation and Regression Analysis introduces statistical techniques that are indispensable to historians and enhances the presentation of them with practical examples from scholarly works. (abebooks.com)

###### Meta-regression analysis6

- In order to fill this gap, we perform a Meta-Regression-Analysis (MRA) by examining 1661 efficiency scores retrieved from 120 papers published over the period 2000--2014. (repec.org)
- Efficiency in banking: a meta-regression analysis ," International Review of Applied Economics , Taylor & Francis Journals, vol. 30(1), pages 112-149, January. (repec.org)
- Equilibrium exchange rates in Central and Eastern Europe: A meta-regression analysis ," Journal of Banking & Finance , Elsevier, vol. 30(5), pages 1359-1374, May. (repec.org)
- Equilibrium Exchange Rates in Central and Eastern Europe: A Meta-Regression Analysis ," William Davidson Institute Working Papers Series wp769, William Davidson Institute at the University of Michigan. (repec.org)
- Equilibrium exchange rates in Central and Eastern Europe : A meta-regression analysis ," BOFIT Discussion Papers 4/2005, Bank of Finland, Institute for Economies in Transition. (repec.org)
- Equilibrium Exchange Rates in Central and Eastern Europe: A Meta-Regression Analysis ," CEPR Discussion Papers 4869, C.E.P.R. Discussion Papers. (repec.org)

###### Binary3

- We've seen in this chapter how to build a binary classifier based on Linear Regression and the logistic function. (oreilly.com)
- re: st: Standardization necessary for mediation analysis with binary outcome? (stata.com)
- The book covers, very completely, the nuances of regression modeling with particular emphasis on binary and ordinal logistic regression and parametric and nonparametric survival analysis. (springer.com)

###### Curve7

- The Linear Regression Curve plots a line that best fits the prices specified over a user-defined time period. (commodity.com)
- Think of the Linear Regression Curve as numerous lines, but both extreme ends of the lines are hidden, while the center portion is shown and is connected to other center portions of lines. (commodity.com)
- The Linear Regression Curve is used mainly to identify trend direction and might sometimes be used to generate buy and sell signals. (commodity.com)
- Traders might view the Linear Regression curve as the fair value for the stock, future, or forex currency pair, and any deviations from the curve as buy and sell opportunities. (commodity.com)
- Generally, when price deviates a certain percentage or number of points below the Linear Regression Curve, then a trader might buy, thinking that price will revert back to fair value, which is thought to be the Linear Regression Curve. (commodity.com)
- In a similar manner, when price moves above the Linear Regression Curve by a trader specified percentage or point value, then the trader might sell, believing that price will return back to the Linear Regression Curve. (commodity.com)
- Since the Linear Regression Curve is great at identifying trend direction, if price is trending higher, a trader might only take buy signals when price deviated below the curve. (commodity.com)

###### Commonly7

- Regression Analysis: A Constructive Critique identifies a wide variety of problems with regression analysis as it is commonly used and then provides a number of ways in which practice could be improved. (sagepub.com)
- Soyer and Hogarth's article, 'The Illusion of Predictability,' shows that diagnostic statistics that are commonly provided with regression analysis lead to confusion, reduced accuracy, and overconfidence. (ssrn.com)
- The multiple regression process utilizes commonly employed statistical measures to test the validity of the analysis and results are summarized in text form to be easily understood. (cnet.com)
- To be able to define commonly used terms in regression analysis and non-parametric statistics. (york.ac.uk)
- Regression analysis is a commonly used statistical methodology. (childrenshospital.org)
- It is written in a clear and direct style…definitely a valuable reference for modern applications of commonly used regression techniques. (springer.com)
- While it utilizes a range of commonly employed statistical measures to test the validity of the analysis, results are summarized in layman's terms for ease of use. (business-spreadsheets.com)

###### Parametric2

- To provide understanding and skills in using linear and logistic regression and non-parametric statistics. (york.ac.uk)
- Demonstrate understanding of the principles underlying inferential statistics with an emphasis on linear and logistic regression and non-parametric statistics. (york.ac.uk)

###### Support vector regression1

- D. Basak , S. Pal and D. C. Patranabis , Support vector regression, Neural Information Processing-Letters and Reviews , 11 (2007), 203-224. (aimsciences.org)

###### Linear Regression Channel4

- This page is about the Linear Regression Channel. (commodity.com)
- Other confirmation signs like prices closing back inside the linear regression channel might be used to initiate potential buy or sell orders. (commodity.com)
- When price closes outside of the Linear Regression Channel for long periods of time, this is often interpreted as an early signal that the past price trend may be breaking and a significant reversal might be near. (commodity.com)
- Arguably the most popular usage of the Linear Regression concept is the Linear Regression Channel, often used by large institutions. (commodity.com)

###### Statistical analyses1

- Rabe-Hesketh, S. and Everitt, B. A handbook of statistical analyses using Stata . (york.ac.uk)

###### Quantile regression1

- Applied Statistical Theory: Quantile Regression. (pearltrees.com)

###### Semiparametric regression1

- A semiparametric regression imputation estimator and an empirical likelihood based one for the mean of the response variable are defined. (hu-berlin.de)

###### Perform a regression1

- What is regression analysis and what does it mean to perform a regression? (surveygizmo.com)

###### Multivariate Statistics1

- My teaching focus is in mathematical economics, including multivariate statistics, regression , and convex analysis . (wyzant.com)

###### Seemingly unrelated1

- In seemingly unrelated regression (SUR), each response variable is a function of a subset of the exogenous series, but not of any endogenous variable. (mathworks.com)

###### Applications of regression1

- The book places a unique emphasis on the practical and contemporary applications of regression modeling rather than the mathematical theory. (ecampus.com)

###### Predict3

- Co-expression analysis is widely used to predict gene function and to identify functionally related gene sets. (nature.com)
- I am using regression to predict the energy consumption (watt/mile) of an electric car based on a number of parameters such as average velocity, max velocity, average acceleration, the number of stops per mile etc. (physicsforums.com)
- Consider using logistic analysis if you would like to predict discrete outcomes. (outsource2india.com)