Logistic random-effects models are often employed in the analysis of correlated binary data. However, fitting these models is challenging, since the marginal distribution of the response variables is analytically intractable. Often, the random effects are treated as missing data for constructing...

A semiparametric mixture model is characterized by a non-parametric mixing distribution <b><scriptface>Q</scriptface></b> (with respect to a parameter <b>"θ"</b>) and a structural parameter <b>"β"</b> common to all components. Much of the literature on mixture models has focused on fixing <b>"β"</b> and estimating <scriptface>Q</scriptface>. However, this can lead to...

In many biomedical studies, we are interested in comparing treatment effects with an inherent ordering. We propose a "quadratic score test" (QST) based on a quadratic inference function for detecting an order in treatment effects for correlated data. The quadratic inference function is similar...