Studying individual data types in isolation provides only limited and incomplete answers to
complex biological questions and particularly falls short in revealing sufficient mechanistic …

Using a generalized estimating equation (GEE) can lead to a bias in regression coefficients
for a small sample or sparse data. The bias‐corrected GEE (BCGEE) and penalized GEE …

Logistic regression is a powerful and widely used analytical tool in linguistics for modelling a
binary outcome variable against a set of explanatory variables. One challenge that can arise …

Objective To assess the time course and risk factors for conversion of incomplete retinal
pigment epithelium and outer retina atrophy (iRORA) to complete retinal pigment epithelium …

The modified Poisson and least‐squares regression analyses for binary outcomes have
been widely used as effective multivariable analysis methods to provide risk ratio and risk …

Background Separation or monotone likelihood may exist in fitting process of the
accelerated failure time (AFT) model using maximum likelihood approach when sample size …

Semiparametric probabilistic index models allow for the comparison of two groups of
observations, whilst adjusting for covariates, thereby fitting nicely within the framework of …

Background Longitudinal ordinal data are commonly analyzed using a marginal
proportional odds model for relating ordinal outcomes to covariates in the biomedical and …

Objectives In this study, we evaluate how to estimate diagnostic test accuracy (DTA)
correctly in the presence of longitudinal patient data (ie, repeated test applications per …

Background The generalized estimating equation (GEE) method is widely used for
analyzing longitudinal and clustered data. Although the GEE estimate for regression …