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.
FREE Two-Day Shipping for students on millions of items. Learn more |
| |||||||||||||||
Book Description
Editorial Reviews
From the Publisher
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.
From the Back Cover
The Wiley Classics Library consists of selected books that have become recognized classics in their respective fields. With these new unabridged and inexpensive editions, Wiley hopes to extend the life of these important works by making them available to future generations of mathematicians and scientists.
--This text refers to the
Paperback
edition.
Product Details
Would you like to update product info or give feedback on images?
|
More About the Author
Discover books, learn about writers, read author blogs, and more.
Customer Reviews
|
Share your thoughts with other customers:
|
||||||||||||||||||||||
|
Most Helpful Customer Reviews
25 of 25 people found the following review helpful:
5.0 out of 5 stars
great introduction to multiple imputation and first by the inventor of the technique,
By
This review is from: Multiple Imputation for Nonresponse in Surveys (Wiley Series in Probability and Statistics) (Hardcover)
This book is a companion to the text by Rubin and Little. It specializes in one particular technique (multiple imputation)that has been highly successful particularly in nonrespnse surveys. Rubin has had a lot of good practical experience in missing data from his years of doing survey research at the Education Testing Service (ETS). He share this experience, knowledge and original ideas in this excellent text!
Share your thoughts with other customers: Create your own review
|
|
Inside This Book
(learn more)
First Sentence:
In a census of a population, an attempt is made to collect information from each unit in the population. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
imputation task, posterior probability coverage, posited response mechanism, repeated significance levels, proper imputation methods, nonignorable model, probability sampling mechanism, nonmonotone patterns, randomization perspective, ignorable sampling, nonmonotone missingness, repeated imputations, ignorable nonresponse, actual posterior distribution, mixture modeling approach, handling nonresponse, recipiency status, normal reference distribution, proper imputations, exact match file, randomization inference, single imputation, initial nonrespondents, using multiple imputation, completed data sets Key Phrases - Capitalized Phrases (CAPs): (learn more)
Census Bureau, Monte Carlo, Current Population Survey, Repeat Problem, Prove Result, Yobs Rinc, Normative Aging Study, United States, Imputation Number, Yobs Ymis New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
In a census of a population, an attempt is made to collect information from each unit in the population. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
imputation task, posterior probability coverage, posited response mechanism, repeated significance levels, proper imputation methods, nonignorable model, probability sampling mechanism, nonmonotone patterns, randomization perspective, ignorable sampling, nonmonotone missingness, repeated imputations, ignorable nonresponse, actual posterior distribution, mixture modeling approach, handling nonresponse, recipiency status, normal reference distribution, proper imputations, exact match file, randomization inference, single imputation, initial nonrespondents, using multiple imputation, completed data sets Key Phrases - Capitalized Phrases (CAPs): (learn more)
Census Bureau, Monte Carlo, Current Population Survey, Repeat Problem, Prove Result, Yobs Rinc, Normative Aging Study, United States, Imputation Number, Yobs Ymis New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Citations (learn more)
This book cites 18
books:
See all 18 books this book cites
100
books
cite this book:
See all 100 books citing this book
- Bayesian Inference (International Library of Critical Writings in Econometrics) by Nicholas G. Polson on page 47, and Back Matter
- Survey Sampling (Wiley Classics Library) by Leslie Kish in Back Matter
- The Design of Experiments by Ronald A. Fisher in Back Matter
- Bayesian Inference in Statistical Analysis (Wiley Classics Library) by George E. P. Box in Back Matter
- Multiple Imputation for Nonresponse in Surveys (Wiley Classics Library) by Donald B. Rubin in Front Matter
See all 18 books this book cites
- Statistical Methods for Quality of Life Studies: Design, Measurements and Analysis by Mounir Mesbah on page 337, and page 351
- Nonsampling Error in Surveys by Judith T. Lessler in Back Matter (1), and Back Matter (2)
- Data Quality Control (Statistics: A Series of Textbooks and Monographs) by Gunar E. Liepins on page 166, and page 353
- Bootstrap Methods: A Practitioner's Guide (Wiley Series in Probability and Statistics) by Michael R. Chernick on page 227, and Back Matter
- Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives (Wiley Series in Probability and Statistics) by Andrew Gelman in Back Matter (1), and Back Matter (2)
See all 100 books citing this book
Books on Related Topics
(learn more)
|
What Other Items Do Customers Buy After Viewing This Item?
Tags Customers Associate with This Product(What's this?)Click on a tag to find related items, discussions, and people.
|
Sell a Digital Version of This Book in the Kindle Store
If you are a publisher or author and hold the digital rights to a book, you can sell a digital version of it in our Kindle Store.
Learn more
Customer Discussions
|
This product's forum
Active discussions in related forums
Search Customer Discussions
|
Related forums
|
