97
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Book: not found

      Applied Missing Data Analysis

      Read this book at

      Buy book Bookmark
          There is no author summary for this book yet. Authors can add summaries to their books on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          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.

          Related collections

          Author and book information

          Book
          23 April 2010
          5bcaf6e3-cf73-4fad-84ce-9573c5a9cae4
          1606236407 9781606236406
          History
          Page count
          Pages: 377

          Comments

          Comment on this book