Statistical Models in Epidemiology, the Environment, and Clinical Trials (Hardcover)

Foreword.- Preface.- Sensitivity analysis for selection bias and unmeasured confounding in missing data and causal inference models.- Marginal structural models versus structural nested models as tools for causal inference.- Nonparametric locally efficient estimation of the treatment specific survival distribution with right censored data and covariates in observational studies.- Estimation of disease rates in small areas: A new mixed model for spatial dependence.- Markov chain Monte Carlo methods for clustering in case event and count data in spatial epidemiology.- A simulation study of the epidemiological impact of air pollution: Diagnostics of the confounding effects for generalized linear models.- The use of reference priors and Bayes factors in the analysis of clinical trials.- Surrogate endpoints in cancer clinical trials.- List of Participants.