Multiple Imputation of Missing Data in Practice: Basic Theory and Analysis Strategies

ISBN-13: 9781498722063 / Angielski / Twarda / 2021 / 476 str.

Yulei He; Guangyu Zhang; Chiu-Hsieh Hsu

Opis

Multiple Imputation of Missing Data in Practice: Basic Theory and Analysis Strategies provides a comprehensive introduction to the multiple imputation approach to missing data problems that are often encountered in data analysis.

Spis treści

1. Introduction. 2. Statistical Background. 3. Multiple Imputation Analysis: Basics. 4. Multiple Imputation for Univariate Missing Data: Parametric Methods. 5. Multiple Imputation for Univariate Missing Data: Robust Methods. 6. Multiple Imputation for Multivariate Missing Data: the Joint Modeling Approach. 7. Multiple Imputation for Multivariate Missing Data: the Fully Conditional Specification Approach. 8. Multiple Imputation in Survival Data Analysis. 9. Multiple Imputation for Longitudinal Data. 10. Multiple Imputation Analysis for Complex Survey Data. 11. Multiple Imputation for Data Subject to Measurement Error. 12. Multiple Imputation Diagnostics.