Applied Missing Data Analysis

Methodology in the Social Sciences

by Craig K. Enders

Walking readers step by step through complex concepts, this book translates missing data techniques into something that applied researchers and graduate students can understand and utilize in their own research. Enders explains the rationale and procedural details for maximum likelihood estimation, Bayesian estimation, multiple imputation, and models for handling missing not at random (MNAR) data. Easy-to-follow examples and small simulated data sets illustrate the techniques and clarify the underlying principles. The companion website (www.appliedmissingdata.com) includes data files and syntax for the examples in the book as well as up-to-date information on software. The book is accessible to substantive researchers while providing a level of detail that will satisfy quantitative specialists.

382 pages, Hardcover

First published April 23, 2010

Reviews

[Elle · Rating 5 out of 5]

I've been reading a bunch of journal articles about missing data and imputation, but had I known this book would be so clear, concise and thorough, I wouldn't have bothered with the journal articles. I've found a lot of the terminology (types of missing data mechanisms, types of strategies) confusing and not well defined in the literature; this book helped me understand the terminology not only through better descriptions, definitions and examples of the terms, but through Dr. Enders' work in specifically addressing how they differ from one another. This is a great reference for the personal library that I will refer to time and time again!

[Dana]

First two chapters are excellent for conceptually understanding the effects that missing data has on inferences and the various ways missing data has been handled in the past (and why none of those are ideal). I regularly assign these to my students, and they always get a lot out of them.

The remainder of the book explains the multiple imputation method in detail.

[Donald Schopflocher · Rating 5 out of 5]

State of the art, and oriented to psychologists using structural equation methods.