Raymond L. Chambers, David G. Steel, Suojin Wang, Alan Welsh

Maximum Likelihood Estimation for Sample Surveys (eBook, PDF)

• Format: PDF

Produktbeschreibung

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.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 391
• Erscheinungstermin: 2. Mai 2012
• Englisch
• ISBN-13: 9781420011357
• Artikelnr.: 39485892

Autorenporträt

Raymond L. Chambers, David G. Steel, Suojin Wang, Alan Welsh

Inhaltsangabe

Introduction. Maximum likelihood theory for sample surveys. Alternative
likelihood-based methods for sample survey data. Populations with
independent units. Regression models. Clustered populations. Informative
nonresponse. Maximum likelihood in other complicated situations.