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Latent class analysis of survey error / Paul P. Biemer.

By: Biemer, Paul PContributor(s): Wiley InterScience (Online service)Material type: TextTextSeries: Wiley series in survey methodologyPublisher: Hoboken, N.J. : Wiley, 2010Description: 1 online resource (pages .)Content type: text Media type: computer Carrier type: online resourceISBN: 9780470891155; 0470891157; 9780470891148; 0470891149Subject(s): Error analysis (Mathematics) | Sampling (Statistics) | Estimation theory | Mathematics | MATHEMATICS -- General | Error analysis (Mathematics) | Estimation theory | Sampling (Statistics)Genre/Form: Electronic books.Additional physical formats: Print version:: Latent class analysis of survey error.DDC classification: 511/.43 LOC classification: QA275 | .B47 2010Online resources: Wiley Online Library
Contents:
Frontmatter -- Survey Error Evaluation -- A General Model for Measurement Error -- Response Probability Models for Two Measurements -- Latent Class Models for Evaluating Classification Errors -- Further Aspects of Latent Class Modeling -- Latent Class Models for Special Applications -- Latent Class Models for Panel Data -- Survey Error Evaluation: Past, Present, and Future -- Appendix A: Two-Stage Sampling Formulas -- Appendix B: Loglinear Modeling Essentials -- References -- Index -- Wiley Series in Survey Methodology.
Summary: "This book concerns the error in data collected using sample surveys, the nature and magnitudes of the errors, their effects on survey estimates, how to model and estimate the errors using a variety of modeling methods, and, finally, how to interpret the estimates and make use of the results in reducing the error for future surveys. The book focuses on models that are appropriate for categorical data, although there are references to the differences and special problems that arise in the analysis and modeling of error for continuous data. Though the primary modeling method that is described is latent class analysis (LCA), a wide range of related models and applications are also discussed"-- Provided by publisher.
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Frontmatter -- Survey Error Evaluation -- A General Model for Measurement Error -- Response Probability Models for Two Measurements -- Latent Class Models for Evaluating Classification Errors -- Further Aspects of Latent Class Modeling -- Latent Class Models for Special Applications -- Latent Class Models for Panel Data -- Survey Error Evaluation: Past, Present, and Future -- Appendix A: Two-Stage Sampling Formulas -- Appendix B: Loglinear Modeling Essentials -- References -- Index -- Wiley Series in Survey Methodology.

"This book concerns the error in data collected using sample surveys, the nature and magnitudes of the errors, their effects on survey estimates, how to model and estimate the errors using a variety of modeling methods, and, finally, how to interpret the estimates and make use of the results in reducing the error for future surveys. The book focuses on models that are appropriate for categorical data, although there are references to the differences and special problems that arise in the analysis and modeling of error for continuous data. Though the primary modeling method that is described is latent class analysis (LCA), a wide range of related models and applications are also discussed"-- Provided by publisher.

Includes bibliographical references (pages 353-368) and index.

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