Multiple Imputation and its Application

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 setsCareful discussion of  key conceptsA range of examples illustrating the key ideasPractical  advice on using multiple imputationExercises and examples designed for  use in the classroom and/or private study
Written for applied  researchers looking to use multiple imputation with confidence, and for  methods researchers seeking an accessible overview of the topic,  Multiple Imputation and its Application will also earn a place in the  libraries of graduate students undertaking quantitative analyses.