Malaria is a major public health problem. An effective vaccine against malaria is actively being sought. We formulate a potential outcomes definition of the efficacy of a malaria vaccine for preventing fever. A challenge in estimating this efficacy is that there is no sure way to determine...

Multistate modeling methods are well-suited for analysis of some chronic diseases that move through distinct stages. The memoryless or Markov assumptions typically made, however, may be suspect for some diseases, such as hepatitis C, where there is interest in whether prognosis depends on...

A method for clustering incomplete longitudinal data, and gene expression time course data in particular, is presented. Specifically, an existing method that utilizes mixtures of multivariate Gaussian distributions with modified Cholesky-decomposed covariance structure is extended to accommodate...

We propose statistical methods for comparing phenomics data generated by the Biolog Phenotype Microarray (PM) platform for high-throughput phenotyping. Instead of the routinely used visual inspection of data with no sound inferential basis, we develop two approaches. The first approach is based...

Lately, bivariate zero-inflated (BZI) regression models have been used in many instances in the medical sciences to model excess zeros. Examples include the BZI Poisson (BZIP), BZI negative binomial (BZINB) models, etc. Such formulations vary in the basic modeling aspect and use the EM algorithm...

Regression models for functional responses and scalar predictors are often fitted by means of basis functions, with quadratic roughness penalties applied to avoid overfitting. The fitting approach described by Ramsay and Silverman in the 1990s amounts to a penalized ordinary least squares...

When patients are monitored for potentially recurrent events such as infections or tumor metastases, it is common for clinicians to ask patients to come back sooner for follow-ups based on the results of the most recent exam. This means that subjects' observation times will be irregular and...

A concrete example of the collaborative double-robust targeted likelihood estimator (C-TMLE) introduced in a companion article in this issue is presented, and applied to the estimation of causal effects and variable importance parameters in genomic data. The focus is on non-parametric estimation...

Estimating treatment effects with observational data requires adjustment for confounding at the analysis stage. This is typically done by including the measured confounders along with the treatment covariate into a regression model for the outcome. Alternatively, it is also possible to adjust...

Dynamic treatment regimes are the type of regime most commonly used in clinical practice. For example, physicians may initiate combined antiretroviral therapy the first time an individual's recorded CD4 cell count drops below either 500 cells/mm3 or 350 cells/mm3. This paper describes an...