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Statistical analysis with missing data / Roderick J.A. Little, Donald B. Rubin.

By: Little, Roderick J.A.
Material type: materialTypeLabelBookSeries: Wiley series in probability and statistics.Publisher: Hoboken, N.J. : Wiley, c2002Edition: 2nd.Description: xv, 381 p. : ill. ; 25 cm.ISBN: 0471183865; 9780471183860.Subject(s): TIME SERIES | DATA MANAGEMENT | LIKELIHOOD | STATISTICAL ANALYSISHoldings: GRETA POINT: 519.5 STA
Contents:
Pt. I: Overview and Basic Approaches 1: Introduction 3 2: Missing Data in Experiments 24 3: Complete-Case and Available-Case Analysis, Including Weighting Methods 41 4: Single Imputation Methods 59 5: Estimation of Imputation Uncertainty 75 Pt. II: Likelihood-Based Approaches to the Analysis of Missing Data 6: Theory of Inference Based on the Likelihood Function 97 7: Factored Likelihood Methods, Ignoring the Missing-Data Mechanism 133 8: Maximum Likelihood for General Patterns of Missing Data: Introduction and Theory with Ignorable Nonresponse 164 9: Large-Sample Inference Based on Maximum Likelihood Estimates 190 10: Bayes and Multiple Imputation 200 Pt. III: Likelihood-Based Approaches to the Analysis of Incomplete Data: Some Examples 11: Multivariate Normal Examples, Ignoring the Missing-Data Mechanism 223 12: Robust Estimation 253 13: Models for Partially Classified Contingency Tables, Ignoring the Missing-Data Mechanism 266 14: Mixed Normal and Non-normal Data with Missing Values, Ignoring the Missing-Data Mechanism 292 15: Nonignorable Missing-Data Models 312 References 349 Author Index 365 Subject Index
Holdings
Item type Current library Call number Copy number Status Date due Barcode
BOOK BOOK WELLINGTON BOOKS 519.5 STA 1 Available B03131

Pt. I: Overview and Basic Approaches 1: Introduction 3 2: Missing Data in Experiments 24 3: Complete-Case and Available-Case Analysis, Including Weighting Methods 41 4: Single Imputation Methods 59 5: Estimation of Imputation Uncertainty 75 Pt. II: Likelihood-Based Approaches to the Analysis of Missing Data 6: Theory of Inference Based on the Likelihood Function 97 7: Factored Likelihood Methods, Ignoring the Missing-Data Mechanism 133 8: Maximum Likelihood for General Patterns of Missing Data: Introduction and Theory with Ignorable Nonresponse 164 9: Large-Sample Inference Based on Maximum Likelihood Estimates 190 10: Bayes and Multiple Imputation 200 Pt. III: Likelihood-Based Approaches to the Analysis of Incomplete Data: Some Examples 11: Multivariate Normal Examples, Ignoring the Missing-Data Mechanism 223 12: Robust Estimation 253 13: Models for Partially Classified Contingency Tables, Ignoring the Missing-Data Mechanism 266 14: Mixed Normal and Non-normal Data with Missing Values, Ignoring the Missing-Data Mechanism 292 15: Nonignorable Missing-Data Models 312 References 349 Author Index 365 Subject Index

GRETA POINT: 519.5 STA

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