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This is the preliminary program for the 2007 Joint Statistical
Meetings in Salt Lake City, Utah.
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The views expressed here are those of the individual authors and not necessarily those of the ASA or its board, officers, or staff. Back to main JSM 2007 Program page |
= Applied Session,
= Theme Session,
= Presenter| CE_04C | Sat, 7/28/07, 8:30 AM - 5:00 PM | CC-151 F |
| Latent Class Analysis of Survey Error - Continuing Education - Course | ||
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Section on Survey Research Methods, ASA |
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| Instructor(s): Paul Biemer, RTI International/The University of North Carolina at Chapel Hill | ||
| A statistical framework for modeling and estimating classification error in surveys. It begins by examining some of the early models for survey measurement error (Census Bureau models; Kish model; etc.) and demonstrating their similarities, strengths and weaknesses. Then these models are cast in a general latent class modeling (LCM) framework where the true values of a variable are assumed to be unobserved (latent) and a survey response constitutes a single indicator of the latent variable. The parameters of the model include the target population proportions for a categorical variable to be estimated in the survey and the probabilities of misclassification; for example, for dichotomous variables, the false positive and false negative probabilities. Survey item reliability and construct validity as well as estimator bias are defined and interpreted in this context. Methods for estimating the model parameters and issues of model identifiability will be discussed. A number of examples and illustrations will be presented to demonstrate the estimation methods and the interpretation of the latent class analysis results. The utility of the models for evaluating and improving survey data quality will also be discuss and demonstrated. The course will introduce the students to the lEM software for fitting a wide-range of LCMs which can be downloaded from the Web at no charge. | ||
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JSM 2007
For information, contact jsm@amstat.org
or phone (888) 231-3473. If you have questions about the Continuing Education program,
please contact the Education Department. |