Regression Methods in Biostatistics - 2nd Ed (2012) Pdf Free Download

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In the second edition of Regression Methods in Biostatistics: Linear, Logistic, Survival, and Repeated Measures Models, we have substantially revised and expanded the core chapters of the first edition, and added two new chapters. The first of these, Chap. 9, on strengthening causal inference, introduces potential outcomes, average causal effects, and two primary methods for estimating these effects, what we call potential outcomes estimation and inverse probability weighting. It also covers propensity scores in detail, then more briefly discusses time-dependent exposures, controlled and natural direct effects, instrumental variables, and principal stratification. The second, Chap. 11, on missing data, explains why this is a problem, classifies missingness by mechanism, and discusses the shortcomings of some simple approaches. Its focus is on three primary approaches for dealing with missing data: maximum likelihood estimation, multiple imputation, and inverse weighting, and lays out in detail when each of these approaches is most appropriate.

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