<span>The most user-friendly and authoritative resource on missing data has been completely revised to make room for the latest developments that make handling missing data more effective.</span><span> The second edition includes new methods based on factored regressions, newer model-based imputatio
Applied Missing Data Analysis (Methodology In The Social Sciences)
✍ Scribed by Craig K. Enders PhD
- Year
- 2010
- Tongue
- English
- Leaves
- 401
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
✦ Synopsis
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.
✦ Subjects
Финансово-экономические дисциплины;Статистический анализ экономических данных;
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