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This book focuses on two general purpose approaches to data analysis that work well in practice: weighting and imputation. The book takes a very practical approach to the methods, with a number of datasets used to illustrate the key aspects. The datasets are taken from randomized trials, observational studies, and sample surveys. Keeping theoretical details to a minimum, the book is suitable for practitioners with only basic knowledge of statistics. The author’s SAS-based software, which can be used for all the examples, is available online.
This book focuses on two general purpose approaches to data analysis that work well in practice: weighting and imputation. The book takes a very practical appro
Multiple Imputation of Missing Data in Practice: Basic Theory and Analysis Strategies provides a comprehensive introduction to the multiple imputation approach
Missing Data Analysis in Practice provides practical methods for analyzing missing data along with the heuristic reasoning for understanding the theoretical und
Walking readers step by step through complex concepts, this book translates missing data techniques into something that applied researchers and graduate student
An up-to-date, comprehensive treatment of a classic text on missing data in statistics The topic of missing data has gained considerable attention in recent dec
