Maximum Likelihood Estimation for Sample Surveys

In recent years, likelihood methods are increasingly being used to analyze survey data in various disciplines, including the medical, biological, environmental, and social sciences. This book presents an overview of likelihood methods for the analysis of survey data obtained using methods that may r...

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Bibliographic Details
Main Authors Chambers, Raymond L., Steel, David G., Wang, Suojin, Welsh, Alan
Format eBook
LanguageEnglish
Published Milton Chapman and Hall/CRC 2012
CRC Press LLC
CRC Press
Edition1
SeriesMonographs on statistics and applied probability
Subjects
Sampling (Statistics)
Statistical methods
Surveys
Size Biased Sampling
Cutoff Sampling
Maximum Pseudolikelihood
Score Function
Inclusion Probabilities
Sample Inclusion Probabilities
Maximum Likelihood
zTi
Approximate Maximum Likelihood Estimate
Maximum Pseudo-likelihood
Unit Nonresponse
Minimal Sufficient Statistic
Survey Variable
Maximum Pseudo-likelihood Estimate
Conditional Expectation
Missing Information Principle
PSUs
Item Nonresponse
Maximum Sample Likelihood
Finite Population Parameters
Sample Survey Data
CCS
Auxiliary Variable
Pseudolikelihood Estimate
Saddlepoint Approximation
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Summary:In recent years, likelihood methods are increasingly being used to analyze survey data in various disciplines, including the medical, biological, environmental, and social sciences. This book presents an overview of likelihood methods for the analysis of survey data obtained using methods that may result in the sample differing from the population, providing all necessary background material on likelihood inference. The book provides coverage of a range of data types, including multilevel data. Illustrated by numerous worked examples using tractable models, it also addresses advanced topics such as combining data, non-response, and informative sampling.
ISBN:1584886323
9781584886327
DOI:10.1201/b12038