Statistical Analysis with Missing Data
Statistical Analysis with Missing Data
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DOI：
10.2307/2531606
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发表时间：
1988-09
期刊：
影响因子：
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通讯作者：
Roderick J. A. Little;D. Rubin
中科院分区：
文献类型：
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作者：
Roderick J. A. Little;D. Rubin
序言.第一部分：概述和基本方法.引言.实验中的缺失数据.完整情况和可解释情况分析，包括加权方法.单一插补方法.插补不确定性的估计.第二部分：缺失数据分析的基于似然的方法.基于似然函数的推理理论.基于因子化似然的方法，忽略缺失数据机制.缺失数据一般模式的最大似然：介绍和可忽略无应答理论。基于最大似然估计的大样本推断。贝叶斯和多重插补。第三部分：基于似然的缺失数据分析方法：一些常见模型的应用。忽略缺失数据机制的多元正态例子。稳健估计模型。部分分类列联表模型。忽略缺失数据机制。正态和非正态数据与缺失值的混合，忽略缺失数据机制。不可解释的缺失数据模型。参考文献。作者索引。主题索引。
Preface.PART I: OVERVIEW AND BASIC APPROACHES.Introduction.Missing Data in Experiments.Complete-Case and Available-Case Analysis, Including Weighting Methods.Single Imputation Methods.Estimation of Imputation Uncertainty.PART II: 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.Large-Sample Inference Based on Maximum Likelihood Estimates.Bayes and Multiple Imputation.PART III: LIKELIHOOD-BASED APPROACHES TO THE ANALYSIS OF MISSING DATA: APPLICATIONS TO SOME COMMON MODELS.Multivariate Normal Examples, Ignoring the Missing-Data Mechanism.Models for Robust Estimation.Models for Partially Classified Contingency Tables, Ignoring the Missing-Data Mechanism.Mixed Normal and Nonnormal Data with Missing Values, Ignoring the Missing-Data Mechanism.Nonignorable Missing-Data Models.References.Author Index.Subject Index.