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Course Number: V 116, Fall 2009

College/University: Minnesota

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Foreword Preface Sensitivity analysis for selection bias and unmeasured confounding in missing data and causal inference models James M. Robins, Andrea Rotnitzky, and Daniel O. Scharfstein Marginal structural models versus structural nested models as tools for causal inference James M. Robins Nonparametric locally ef cient estimation of the treatment speci c survival distribution with right censored data and...

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Foreword Preface Sensitivity analysis for selection bias and unmeasured confounding in missing data and causal inference models James M. Robins, Andrea Rotnitzky, and Daniel O. Scharfstein Marginal structural models versus structural nested models as tools for causal inference James M. Robins Nonparametric locally ef cient estimation of the treatment speci c survival distribution with right censored data and covariates in observational studies Alan E. Hubbard, Mark J. van der Laan, and James M. Robins Estimation of disease rates in small areas: A new mixed model for spatial dependence Brian G. Leroux, Xingye Lei, and Norman Breslow <a href="/keyword/markov-chain-monte-carlo/" >markov <a href="/keyword/chain-monte-carlo/" ><a href="/keyword/chain-monte/" >chain monte</a> carlo</a> </a> methods for clustering in case event and count data in spatial epidemiology Andrew B. Lawson and Allan B. Clark A simulation study of the epidemiological impact of air pollution: Diagnostics of the confounding effects for generalized linear models Co...