書誌事項

Statistical analysis with missing data

Roderick J.A. Little, Donald B. Rubin

(Wiley series in probability and mathematical statistics, . Applied probability and statistics)

Wiley, c1987

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注記

Includes indexes

内容説明・目次

内容説明

Blending theory and application, this study reviews historical approaches to the subject and provides rigorous yet simple methods for multivariate analysis with missing values. The book goes on to provide a coherent theory for the analysis of problems based on likelihoods derived from statistical models for the data and the missing data mechanism. The theory is applied to a wide range of important missing-data problems. Extensive references, examples and exercises are also provided.

目次

OVERVIEW AND HISTORICAL APPROACHES. Missing Data in Experiments. Quick Methods for Multivariate Data with Missing Values. Nonresponse in Sample Surveys. LIKELIHOOD-BASED APPROACHES TO THE ANALYSIS OF MISSING DATA. Theory of Inference Based on the Likelihood Function. Methods Based on Factoring the Likelihood, Ignoring the Missing Data Mechanism. Maximum Likelihood for General Patterns of Missing Data: Introduction and Theory with Ignorable Nonresponse. Maximum Likelihood Estimation for Multivariate Normal Examples, Ignoring the Missing-Data Mechanism. Models for Partially Classified Contingency Tables, Ignoring the Missing Data Mechanism. Mixed Normal and Nonrational Data with Missing Values, Ignoring the Missing-Data Mechanism. Nonignorable Nonresponse Models. The Model-Based Approach to Survey Nonresponse. Index.

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