This handbook presents many methodological advances and the latest applications of missing data methods in empirical research. It outlines a general taxonomy of missing data mechanisms and their implications for analysis and describes alternatives for estimating models when data are missing. The book covers a range of approaches that assess the sensitivity of inferences to alternative assumptions about the missing data process. It also discusses...