Essex Summer School in
Social Science Data Analysis

Allan L. McCutcheon

Allan L. McCutcheon holds the Donald O. Clifton Chair of Survey Science, and is Professor of Statistics and Survey Research & Methodology at the University of Nebraska at Lincoln; he is also the founding Director of the Gallup Research Centre. He has taught workshops on categorical data analysis and public opinion polling at the ICPSR Summer Programme at the University of Michigan; the Central Archive for Empirical Social Research at the University of Cologne; the Central European University in Budapest; the Catholic University of Brussels and the Institute for Advanced Studies in Vienna. He is, with Jacques Hagenaars, co-editor of Applied Latent Class Analysis (Cambridge University Press. 2002), and author of Latent Class Analysis (Sage 1986). He has also published several articles applying log-linear and latent class models to substantive issues in social, political, and cross-cultural research. He is an elected fellow of the American Statistical Association and the Royal Statistical Society.

2K Latent Class Analysis

Allan McCutcheon, University of Nebraska at Lincoln
23 July - 3 August (two week course / 35 hrs)

Detailed Course Outline [PDF]

Course Content

This course provides participants with a practical, working knowledge of one of the major approaches to categorical data analysis and market segmentation research: latent class analysis. The latent class model (LCM) provides one of the most important approaches for understanding relationships among a wide variety of respondents and consumer attitudes and behaviour. The LCM facilitates the construction and testing of models of respondent types (e.g., market segments), and helps in characterizing the nature of complex groups. In addition to the basic LCM, attention is given to modelling longitudinal data, as well as to the inclusion of predictor and outcome variables related to the segments. We examine the conceptual and methodological foundations of market segmentation, with several specific applications of the latent class and related models to a variety of data types.

Course Objectives

The course introduces participants to the conceptual and methodological foundations of the latent class model and its linkages to market segmentation, as well as its application to a variety of related social and political science problems. The expectation is that, at the end of the course, participants will be able successfully to conduct research using latent class analysis, as well as be prepared to pursue self-directed study in the area.

Course Prerequisites

Participants should have some understanding of basic probability and contingency tables (cross-tabulation), as well as basic algebra. A solid understanding of the logic of causality, such as found in regression and factor analysis, is also necessary. The mathematics/statistics underlying the logic of regression and factor analysis are useful, but not essential.

Remedial Reading

Davis, J. A. 1986. The Logic of Causal Order. Sage. QASS No.55.

Representative Background Reading

McCutcheon, A., and Mills, C. 1998. ‘Categorical data analysis: Log-linear and latent class models’, in E.Scarbrough and E. Tanenbaum (Eds.), Research Strategies in the Social Sciences. Oxford University Press.

McCutcheon, A. 2002. ‘Basic Concepts and Procedures in Single- and Multiple-Group Latent Class Analysis’, in J. Hagenaars and A. McCutcheon (Eds.), Applied Latent Class Analysis. Cambridge University Press.

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