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Missing Data Analysis in Practice presents smart methods for analyzing missing data along with the heuristic reasoning for understanding the theoretical underpinnings. Drawing on his 25 years of experience researching, instructing, and consulting in quantitative areas, the creator presents every frequentist and Bayesian views. He describes easy-to-implement approaches, the underlying assumptions, and smart means for assessing these assumptions. Actual and simulated data items illustrate very important concepts, with the data items and codes on the market on-line. The e ebook underscores the occasion of missing data methods and their adaptation to smart points. It primarily focuses on the usual missing data draw back. The creator moreover reveals how one can use the missing data framework in many alternative statistical points, equal to measurement error, finite inhabitants inference, disclosure limitation, combing information from quite a few data sources, and causal inference. |
