Multiple Imputation for Nonresponse in Surveys

Donald B. Rubin - Collection Wiley Classics Library

290 pages, parution le 18/08/2004

Ajouter à une liste

Indisponible

Résumé

Demonstrates how nonresponse in sample surveys and censuses can be handled by replacing each missing value with two or more multiple imputations. Clearly illustrates the advantages of modern computing to such handle surveys, and demonstrates the benefit of this statistical technique for researchers who must analyze them. Also presents the background for Bayesian and frequentist theory. After establishing that only standard complete-data methods are needed to analyze a multiply-imputed set, the text evaluates procedures in general circumstances, outlining specific procedures for creating imputations in both the ignorable and nonignorable cases. Examples and exercises reinforce ideas, and the interplay of Bayesian and frequentist ideas presents a unified picture of modern statistics.

L'auteur - Donald B. Rubin

Donald B. Rubin , PhD, is a John L. Loeb Professor of Statistics at Harvard University in Cambridge, MA. He was named 2000-2001 Statistician of the Year by the Chicago Chapter of ASA. His research interests include causal inference in experiments and observational studies, developing and applying statistical models to data in a variety of scientific disciplines, and the application of Bayesian and empirical Bayesian techniques.

Sommaire

Introduction
Statistical Background
Underlying Bayesian Theory
Randomization-Based Evaluations
Procedures with Ignorable Nonresponse
Procedures with Nonignorable Nonresponse
Appendix I Report Written for the Social Security Administration in 1977
Appendix II Report Written for the Census Bureau in 1983

Voir tout

Replier

Caractéristiques techniques

	PAPIER
Éditeur(s)	Wiley
Auteur(s)	Donald B. Rubin
Collection	Wiley Classics Library
Parution	18/08/2004
Nb. de pages	290
Format	15,5 x 23,5
Couverture	Broché
Poids	450g
Intérieur	Noir et Blanc
EAN13	9780471655749