A New Formulation for Latent Class Models

33 Pages Posted: 5 Jul 2014

See all articles by Sarah Brown

Sarah Brown

University of Sheffield - Department of Economics; IZA Institute of Labor Economics

William H. Greene

New York University Stern School of Business

Mark N. Harris

Curtin University

Abstract

Latent class, or finite mixture, modelling has proved a very popular, and relatively easy, way of introducing much-needed heterogeneity into empirical models right across the social sciences. The technique involves (probabilistically) splitting the population into a finite number of (relatively homogeneous) classes, or types. Within each of these, typically, the same statistical model applies, although these are characterised by differing parameters of that distribution. In this way, the same explanatory variables can have differing effects across the classes, for example. A priori, nothing is known about the behaviours within each class; but ex post, researchers invariably label the classes according to expected values, however defined, within each class. Here we propose a simple, yet effective, way of parameterising both the class probabilities and the statistical representation of behaviours within each class, that simultaneously preserves the ranking of such according to class-specific expected values and which yields a parsimonious representation of the class probabilities.

Keywords: latent class models, finite mixture models, ordered probability models, expected values, body mass index

JEL Classification: C3, D1, I1

Suggested Citation

Brown, Sarah and Greene, William H. and Harris, Mark N., A New Formulation for Latent Class Models. IZA Discussion Paper No. 8283. Available at SSRN: https://ssrn.com/abstract=2462715

Sarah Brown (Contact Author)

University of Sheffield - Department of Economics

9 Mappin Street
Sheffield, S1 4DT
United Kingdom

IZA Institute of Labor Economics

P.O. Box 7240
Bonn, D-53072
Germany

William H. Greene

New York University Stern School of Business ( email )

44 West 4th Street
Suite 9-160
New York, NY NY 10012
United States
212-998-0876 (Phone)

HOME PAGE: http://people.stern.nyu.edu/wgreene

Mark N. Harris

Curtin University ( email )

Kent Street
Bentley
Perth, WA WA 6102
Australia

HOME PAGE: http://business.curtin.edu.au/contact/staff_directory/?profile=Mark-Harris

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