Latent Class Analysis of Survey Error

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Latent Class Analysis of Survey Error

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Combining theoretical, methodological, and practical aspects,Latent Class Analysis of Survey Error successfully guides readersthrough the accurate interpretation of survey results for qualityevaluation and improvement. This book is a comprehensive resourceon the key statistical tools and techniques employed during themodeling and estimation of classification errors, featuring aspecial focus on both latent class analysis (LCA) techniques andmodels for categorical data from complex sample surveys.

Drawing from his extensive experience in the field of surveymethodology, the author examines early models for surveymeasurement error and identifies their similarities and differencesas well as their strengths and weaknesses. Subsequent chapterstreat topics related to modeling, estimating, and reducing errorsin surveys, including:
* Measurement error modeling for categorical data
* The Hui-Walter model and other methods for two indicators
* The EM algorithm and its role in latent class 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 andunequal probability samples with nonresponse
* The current state of LCA and MLCA (multilevel latent class analysis), and an insightful discussion on areas for furtherresearch

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