Abstract #301349

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JSM 2003 Abstract #301349
Activity Number: 449
Type: Contributed
Date/Time: Thursday, August 7, 2003 : 8:30 AM to 10:20 AM
Sponsor: Social Statistics Section
Abstract - #301349
Title: Comparison of Alternative Latent Class Clusterings of Survey Data
Author(s): Michael D. Larsen*+
Companies: University of Chicago
Address: Dept. of Statistics-Eckhart Hall 124, Chicago, IL, 60637-1514,
Keywords: adjusted Rand index ; mixture models ; model selection ; number of classes ; variable selection ; stability of clusters
Abstract:

The U.S. National Science Foundation's SESTAT database is created from biennial surveys that are representative of U.S. scientists and engineers and provides detailed information about the employment, educational, and demographic characteristics of U.S. scientists and engineers. Several sets of qualitative questions focus on motivations for career decisions. These career choice questions will be analyzed using latent class analysis. The classes then will be studied in terms of salary, gender and minority representation, and other factors. Comparisons will be made to other clustering techniques. In particular, various methods for describing the quality of clustering and for comparing alternative cluster solutions will be described and illustrated.

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