The most up-to-date edition of a bestselling guide to analyzing partially observed data
In this comprehensively revised Second Edition of Multiple Imputation and its Application, a team of distinguished statisticians delivers an overview of the issues raised by missing data, the rationale for multiple imputation as a solution, and the practicalities of applying it in a multitude of settings.
With an accessible and carefully structured presentation aimed at quantitative researchers, Multiple Imputation and its Application is illustrated with a range of examples and offers key mathematical details. The book includes a wide range of theoretical and computer-based exercises, tested in the classroom, which are especially useful for users of R or Stata. Readers will find:
- A comprehensive overview of one of the most effective and popular methodologies for dealing with incomplete data sets
- Careful discussion of key concepts
- A range of exampl
