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Book Cover
E-book
Author Allison, Paul David.

Title Missing data / Paul D. Allison
Published Thousand Oaks [Calif.] ; London : SAGE, [2002]
©2002
Online access available from:
Sage Research Methods Online Books    View Resource Record  

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Description 1 online resource (vi, 91 pages) : illustrations
Series Quantitative applications in the social sciences ; 136
Quantitative applications in the social sciences ; 136
Contents 1. Introduction -- 2. Assumptions ; Missing Completely at Random ; Missing at Random ; Ignorable ; Nonignorable -- 3. Conventional Methods ; Listwise ; Deletion; Pairwise Deletion ; Dummy Variable Adjustment ; Imputation -- 4. Maximum Likelihood ; Review of Maximum Likelihood ; ML With Missing Data ; Contingency Table Data ; Linear Models With Normally Distributed Data ; The EM Algorithm ; EM Example ; Direct ML ; Direct ML Example -- 5. Multiple Imputation: Bascis ; Single Random Imputation ; Multiple Random Imputation ; Allowing for Random Variation in the Parameter Estimates ; Multiple Imputation Under the Multivariate Normal Model ; Data Augmentation for the Multivariate Normal Model ; Convergence in Data Augmentation ; Sequential Verses Parallel Chains of Data Augmentation ; Using the Normal Model for Nonnormal or Categorical Data ; Exploratory Analysis -- 6. Multiple Imputation: Complications ; Interactions and Nonlinearities in MI ; Compatibility of the Imputation Model and the Analysis Model ; Role of the Dependent Variable in Imputation ; Using Additional Variables in the Imputation Process ; Other Parametric Approaches to Multiple Imputation ; Nonparametric and Partially Parametric Methods ; Sequential Generalized Regression Models ; Linear Hypothesis Tests and Likelihood Ratio Tests -- 7. Nonignorable Missing Data ; Two Classes of Models ; Heckman's Model for Sample Selection Bias ; ML Estimation With Pattern-Mixture Models ; Multiple Imputation With Pattern-Mixture Models
Summary Using numerous examples and practical tips, this book offers a non-technical explanation of the standard methods for missing data (such as listwise or casewise deletion) as well as two newer methods, maximum likelihood and multiple imputation
Bibliography Includes bibliographical references
Includes bibliographical references and index
Notes Print version record
Subject Missing observations (Statistics)
Form Electronic book
ISBN 9781412985079 (ebook)
1412985072 (ebook)
9780761916727
9781452207902
1452207909
Other Titles Available from some providers with title: Sage research methods online