Biomaterial Database

[Analysis of ordinal repeated measures data using generalized estimating equation]. 2006

Xiang Liu, and Ju-ying Zhang

Department of Health Statistics, West China School of Public Health, Sichuan University, Chengdu 610041, China.

OBJECTIVE To explore the application of the generalized estimating equation in the ordinal repeated measures data and hence provide methodology reference for the analysis of repeated measures data in the clinical trials. METHODS An example was illustrated by modeling generalized estimating equation using the GENMOD command in comparison with the independent logistic regression. RESULTS All parameters and their standard error were estimated, so every factor could be dealt with intuitive estimation of parameter. The standard errors of coefficients in generalized estimating equation are generally greater than that in independent logistic regression. CONCLUSIONS Generalized estimating equation can solve the correlation between the dependent data by using working correlation matrix, and it can control strata correlation, repeated measures factor and other confounding factors effectively, so generalized estimating equation provides an effective method for the ordinal repeated measures data.

UI	MeSH Term	Description	Entries
D002986	Clinical Trials as Topic	Works about pre-planned studies of the safety, efficacy, or optimum dosage schedule (if appropriate) of one or more diagnostic, therapeutic, or prophylactic drugs, devices, or techniques selected according to predetermined criteria of eligibility and observed for predefined evidence of favorable and unfavorable effects. This concept includes clinical trials conducted both in the U.S. and in other countries.	Clinical Trial as Topic
D003627	Data Interpretation, Statistical	Application of statistical procedures to analyze specific observed or assumed facts from a particular study.	Data Analysis, Statistical,Data Interpretations, Statistical,Interpretation, Statistical Data,Statistical Data Analysis,Statistical Data Interpretation,Analyses, Statistical Data,Analysis, Statistical Data,Data Analyses, Statistical,Interpretations, Statistical Data,Statistical Data Analyses,Statistical Data Interpretations
D016014	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.	Linear Regression,Log-Linear Models,Models, Linear,Linear Model,Linear Regressions,Log Linear Models,Log-Linear Model,Model, Linear,Model, Log-Linear,Models, Log-Linear,Regression, Linear,Regressions, Linear
D016015	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.	Logistic Regression,Logit Models,Models, Logistic,Logistic Model,Logistic Regressions,Logit Model,Model, Logistic,Model, Logit,Models, Logit,Regression, Logistic,Regressions, Logistic