For analyses of longitudinal repeated‐measures data, statistical methods include the
random effects model, fixed effects model and the method of generalized estimating …

The method of generalized estimating equations (GEE) is often used to analyze longitudinal
and other correlated response data, particularly if responses are binary. However, few …

We provide sufficient conditions for estimating from longitudinal data the causal effect of a
time-dependent exposure or treatment on the marginal probability of response for a …

Longitudinal data sets are comprised of repeated observations of an outcome and a set of
covariates for each of many subjects. One objective of statistical analysis is to describe the …

Longitudinal studies play a prominent role in biomedical and sociological research.
Generalized estimating equations (GEE) provide a regression methodology to analyze the …

In biomedical research, we are often interested in quantifying the relationship between an
exposure and an outcome.“Odds” and “Risk” are the most common terms which are used as …

Analysis of data with repeated measures is often accomplished through the use of
generalized estimating equations (GEE) methodology. Although methods exist for assessing …

The analysis of data from longitudinal studies requires special techniques, which take into
account the fact that the repeated measurements within one individual are correlated. In this …

Meta-analysis plays an important role in the analysis and interpretation of clinical trials in
medicine and of trials in the social sciences but is of importance in other fields (eg, particle …

Derivation of the minimum sample size is an important consideration in an applied research
effort. When the outcome is measured at a single time point, sample size procedures are …