Many medical studies collect biomarker data to gain insight into the biological mechanisms underlying both acute and chronic diseases. These markers may be obtained at a single point in time to aid in the diagnosis of an illness or may be collected longitudinally to provide information on the...

Longitudinal censoring is a common artifact when evaluating biomarkers and an obstacle to overcome when jointly investigating the longitudinal nature of the data and the impact on the survival prognoses of a study population. To fully appreciate the complexity of this scenario one has to devise...

In a longitudinal study of biomarker data collected during a hospital stay, observations may be missing due to administrative reasons, the death of the subject or the subject's discharge from the hospital, resulting in non-ignorable missing data. Standard likelihood-based methods for the...

Survival analysis has been used to estimate underlying survival or failure probabilities and to estimate the effects of covariates on survival times. The Cox proportional hazards regression model is the most commonly used approach. However, in practical situations, the assumption of proportional...

In a case-cohort design introduced by Prentice (1986), covariates are assembled only for a subcohort randomly selected from the entire cohort, and any additional cases outside the subcohort. Semiparametric transformation models are considered here for failure time data from the case-cohort...

The Generalized Additive model (GAM) has been used as a standard tool for epidemiologic analysis exploring the effect of air pollution on population health during the last decade as it allows nonparametric relationships between the independent predictors and response. One major concern to the...

Generalized additive model (GAM) with natural cubic splines (NS) has been commonly used as a standard analytical tool in time series studies of health effects of air pollution. Standard model selection procedures used in GAM ignore the uncertainty in model fitting. This may lead to biased...

Adaptive treatment regime is a set of rules that governs the assignment of time-varying treatment based on observed covariates and intermediate response. Treatment choices are made sequentially as patients make transition from one health state to another. Specifically, in two stage randomization...

Many research areas require multiple outcomes. For example, neuropsychological hypotheses may not be testable using a single measure. Similarly, genetic researchers frequently examine multiple markers across the genome. Examining multiple hypotheses requires the use of multiple testing...