Coverart for item
The Resource Statistical analysis with missing data, Roderick J.A. Little, Donald B. Rubin

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

Label
Statistical analysis with missing data
Title
Statistical analysis with missing data
Statement of responsibility
Roderick J.A. Little, Donald B. Rubin
Creator
Contributor
Author
Subject
Genre
Language
eng
Summary
AN UP-TO-DATE, COMPREHENSIVE TREATMENT OF A CLASSIC TEXT ON MISSING DATA IN STATISTICS The topic of missing data has gained considerable attention in recent decades. This new edition by two acknowledged experts on the subject offers an up-to-date account of practical methodology for handling missing data problems. Blending theory and application, authors Roderick Little and Donald Rubin review historical approaches to the subject and describe simple methods for multivariate analysis with missing values. They then provide a coherent theory for analysis of problems based on likelihoods derived from statistical models for the data and the missing data mechanism, and then they apply the theory to a wide range of important missing data problems. Statistical Analysis with Missing Data, Third Edition starts by introducing readers to the subject and approaches toward solving it. It looks at the patterns and mechanisms that create the missing data, as well as a taxonomy of missing data. It then goes on to examine missing data in experiments, before discussing complete-case and available-case analysis, including weighting methods. The new edition expands its coverage to include recent work on topics such as nonresponse in sample surveys, causal inference, diagnostic methods, and sensitivity analysis, among a host of other topics. An updated "classic" written by renowned authorities on the subject Features over 150 exercises (including many new ones) Covers recent work on important methods like multiple imputation, robust alternatives to weighting, and Bayesian methods Revises previous topics based on past student feedback and class experience Contains an updated and expanded bibliography Statistical Analysis with Missing Data, Third Edition is an ideal textbook for upper undergraduate and/or beginning graduate level students of the subject. It is also an excellent source of information for applied statisticians and practitioners in government and industry
Member of
Cataloging source
N$T
http://library.link/vocab/creatorName
Little, Roderick J. A
Dewey number
519.5
Index
index present
LC call number
QA276
LC item number
.L57 2020
Literary form
non fiction
Nature of contents
dictionaries
http://library.link/vocab/relatedWorkOrContributorName
Rubin, Donald B.
Series statement
Wiley series in probability and statistics
http://library.link/vocab/subjectName
  • Mathematical statistics
  • Mathematical statistics
  • Missing observations (Statistics)
  • MATHEMATICS / Applied
  • MATHEMATICS / Probability & Statistics / General
  • Mathematical statistics
  • Missing observations (Statistics)
Label
Statistical analysis with missing data, Roderick J.A. Little, Donald B. Rubin
Instantiates
Publication
Note
Includes index
Antecedent source
unknown
Bibliography note
Includes bibliographical references and indexes
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
Part I Overview and Basic Approaches -- Introduction -- Missing Data in Experiments -- Complete-Case and Available-Case Analysis -- Single Imputation Methods -- Accounting for Uncertainty from Missing Data -- Part II Likelihood-Based Approaches to the Analysis of Data with Missing Values -- Theory of Inference Based on the Likelihood Function -- Factored Likelihood Methods When the Missingness Machanism is Ignorable -- 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 Incomplete Data: Some Examples -- Multivariate Normal Examples, Ignoring the Missingness Mechanism -- Models for Robust Estimation -- Models for Partially Classified Contingency Tables, Ignorning the Missingness Mechanism -- Mixed Normal and Nonnormal Data with Missing Values, Ignoring the Missingness Mechanism -- Missing Not at Random Models
Control code
1090652796
Dimensions
unknown
Edition
Third edition.
Extent
1 online resource.
File format
unknown
Form of item
online
Isbn
9781118595695
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
http://library.link/vocab/ext/overdrive/overdriveId
9781118595695
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
(OCoLC)1090652796
Label
Statistical analysis with missing data, Roderick J.A. Little, Donald B. Rubin
Publication
Note
Includes index
Antecedent source
unknown
Bibliography note
Includes bibliographical references and indexes
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
Part I Overview and Basic Approaches -- Introduction -- Missing Data in Experiments -- Complete-Case and Available-Case Analysis -- Single Imputation Methods -- Accounting for Uncertainty from Missing Data -- Part II Likelihood-Based Approaches to the Analysis of Data with Missing Values -- Theory of Inference Based on the Likelihood Function -- Factored Likelihood Methods When the Missingness Machanism is Ignorable -- 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 Incomplete Data: Some Examples -- Multivariate Normal Examples, Ignoring the Missingness Mechanism -- Models for Robust Estimation -- Models for Partially Classified Contingency Tables, Ignorning the Missingness Mechanism -- Mixed Normal and Nonnormal Data with Missing Values, Ignoring the Missingness Mechanism -- Missing Not at Random Models
Control code
1090652796
Dimensions
unknown
Edition
Third edition.
Extent
1 online resource.
File format
unknown
Form of item
online
Isbn
9781118595695
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
http://library.link/vocab/ext/overdrive/overdriveId
9781118595695
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
(OCoLC)1090652796

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