Clustered failure time data often arise in biomedical studies and a marginal regression modeling approach is often preferred to avoid assumption on the dependence structure within clusters. A novel estimating equation approach is proposed based on a semiparametric marginal proportional hazards...

In this paper, the author investigates optimal designs for multivariate binary regression models used in many clinical experiments. As the computation of a joint likelihood for multiple binary outcomes is often tedious, the author proposes and explores a pseudo-likelihood approach for choosing...

A unified empirical likelihood approach for three Cox-type marginal models dealing with multiple event times, recurrent event times and clustered event times is proposed. The resulting log-empirical likelihood ratio test statistics are shown to possess chi-squared limiting distributions. When...

Notable bias can exist in the empirical covariance matrix of parameter estimates obtained from the quadratic inference function method that incorporates an unstructured working correlation. We therefore derive a bias correction. Via simulation, we show that the proposed correction leads to...

Comparing regression coefficients between models when one model is nested within another is of great practical interest when two explanations of a given phenomenon are specified as linear models. The statistical problem is whether the coefficients associated with a given set of covariates change...

In biomedical studies, the event of interest is often recurrent and within-subject events cannot usually be assumed independent. In addition, individuals within a cluster might not be independent; for example, in multi-center or familial studies, subjects from the same center or family might be...

Health technology assessment often requires the evaluation of interventions which are implemented at the level of the health service organization unit (e.g. GP practice) for clusters of individuals. In a cluster randomized controlled trial (cRCT), clusters of patients are randomized; not each...