Latent Class Analysis of Survey Error (eBook)

Paul P. Biemer (Autor)

eBook Download: PDF

2010 | 1. Auflage
412 Seiten
John Wiley & Sons (Verlag)
978-0-470-89114-8 (ISBN)

Infos

Combining theoretical, methodological, and practical aspects,
Latent Class Analysis of Survey Error successfully guides readers
through the accurate interpretation of survey results for quality
evaluation and improvement. This book is a comprehensive resource
on the key statistical tools and techniques employed during the
modeling and estimation of classification errors, featuring a
special focus on both latent class analysis (LCA) techniques and
models for categorical data from complex sample surveys.

Drawing from his extensive experience in the field of survey
methodology, the author examines early models for survey
measurement error and identifies their similarities and differences
as well as their strengths and weaknesses. Subsequent chapters
treat topics related to modeling, estimating, and reducing errors
in surveys, including:

* Measurement error modeling forcategorical data

* The Hui-Walter model and othermethods for two indicators

* The EM algorithm and its role in latentclass model parameter
estimation

* Latent class models for three ormore indicators

* Techniques for interpretation of modelparameter estimates

* Advanced topics in LCA, including sparse data, boundary values,
unidentifiability, and local maxima

* Special considerations for analyzing datafrom clustered and
unequal probability samples with nonresponse

* The current state of LCA and MLCA (multilevel latent class
analysis), and an insightful discussion on areas for further
research

Throughout the book, more than 100 real-world examples describe
the presented methods in detail, and readers are guided through the
use of lEM software to replicate the presented analyses. Appendices
supply a primer on categorical data analysis, and a related Web
site houses the lEM software.

Extensively class-tested to ensure an accessible presentation,
Latent Class Analysis of Survey Error is an excellent book for
courses on measurement error and survey methodology at the graduate
level. The book also serves as a valuable reference for researchers
and practitioners working in business, government, and the social
sciences who develop, implement, or evaluate surveys.

Autor

Paul P. Biemer, PhD, is Distinguished Fellow in Statistics at RTI International and Associate Director for Survey Research and Development at the Odum Institute for Research in Social Science at the University of North Carolina at Chapel Hill. An expert in the field of survey measurement error, Dr. Biemer has published extensively in his areas of research interest, which include survey design and analysis; general survey methodology; and nonsampling error modeling and evaluation. He is a coauthor of Introduction to Survey Quality and a coeditor of Telephone Survey Methodology, Survey Measurement and Process Quality, and Measurement Errors in Surveys, all published by Wiley.

Rezensionen

"Biemer (statistics, RTI International and survey research and
development, U. of North Carolina at Chapel Hill) provides a
comprehensive source on the primary statistical tools and
techniques used in the modeling and estimation of classification
errors, with a particular focus on latent class techniques and
models for categorical data from complex sample surveys . . . the
book would be useful as a text for graduate level courses in
measurement error and survey methodology, as well as a reference
for researchers and professionals in business, government, and
social sciences who are responsible for developing, implementing,
or evaluating surveys." (Booknews, 1 April 2011)



"By combining theoretical, methodological and practical aspects
of estimating classification error, the book provides a guide for
the practitioner as well as a text for the student of survey error
evaluation". (RTI International, 18 January 2011)

Produkt-Details

• Erscheint lt. Verlag: 18.10.2010
• Reihe/Serie: Wiley Series in Survey Methodology
• Reihe/Serie: Wiley Series in Survey Methodology
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Mathematik ► Statistik
• Themenwelt: Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik
• Themenwelt: Technik
• Schlagworte: categorical data analysis • Datenanalyse • Datenerhebung • Kategorielle Datenanalyse • Methoden der Daten- u. Stichprobenerhebung • Spezialthemen Statistik • Statistics • Statistics Special Topics • Statistik • Survey Research Methods & Sampling
• ISBN-10: 0-470-89114-9 / 0470891149
• ISBN-13: 978-0-470-89114-8 / 9780470891148