Missing data form a problem in every scientific discipline, yet the techniques required to handle them are complicated and often lacking. One of the great ideas in statistical science-multiple imputation-fills gaps in the data with plausible values, the uncertainty of which is coded in the data itself. It also solves other problems, many of which a

part I|2 pages

I Basics

chapter 1|22 pages


chapter 2|28 pages

Multiple imputation

chapter 3|42 pages

Univariate missing data

chapter 4|28 pages

Multivariate missing data

chapter 5|30 pages

Imputation in practice

chapter 6|16 pages

Analysis of imputed data

part II|2 pages

II Case studies

chapter 7|34 pages

Measurement issues

chapter 8|16 pages

Selection issues

chapter 9|26 pages

Longitudinal data

part III|2 pages

III Extensions

chapter 10|14 pages