Abstract
An overview is provided of recent developments in the use of latent class (LC) models in social science research. Special attention is paid to the application of LC analysis as a factor-analytic tool and as a tool for random-effects modeling. Furthermore, an extension of the LC model to deal with nested data structures is presented.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Agresti, A.: Categorical Data Analysis, 2nd edn. Wiley, New York (2002)
Baum, L.E., Petrie, T., Soules, G., Weiss, N.: A maximization technique occurring in the statistical analysis of probabilistic functions of Markov chains. Annals of Mathematical Statistics 41, 164–171 (1970)
Clogg, C.C., Goodman, L.A.: Latent structure analysis of a set of multidimensional contingency tables. Journal of the American Statistical Association 79, 762–771 (1984)
Formann, A.K.: Linear logistic latent class analysis for polytomous data. Journal of the American Statistical Association 87, 476–486 (1992)
Goldstein, H.: Multilevel statistical models. Halsted Press, New York (1995)
Goodman, L.A.: The analysis of systems of qualitative variables when some of the variables are unobservable: Part I – A modified latent structure approach. American Journal of Sociology 79, 1179–1259 (1974)
Hagenaars, J.A.: Loglinear Models with Latent Variables, Sage University Paper. Sage Publications, Newbury Park (1993)
Hagenaars, J.A., McCutcheon, A.L.: Applied Latent Class Analysis. Cambridge University Press, Cambridge (2002)
Heinen, T.: Latent Class and Discrete Latent Trait Models: Similarities and Differences. Sage Publications, Thousand Oaks (1996)
Kamakura, W.A., Wedel, M., Agrawal, J.: Concomitant variable latent class models for the external analysis of choice data. International Journal of Marketing Research 11, 464–541 (1994)
Lazarsfeld, P.F., Henry, N.W.: Latent Structure Analysis. Houghton Mill, Boston (1968)
Magidson, J., Vermunt, J.K.: Latent class factor and cluster models, bi-plots and related graphical displays. Sociological Methodology 31, 223–264 (2001)
McCutcheon, A.L.: Latent Class Analysis, Sage University Paper. Sage Publications, Newbury Park (1987)
McGrath, K., Waterton, J.: British social attitudes, 1983–1986 panel survey. London: Social and Community Planning Research, Technical Report (1986)
McLachlan, G.J., Peel, D.: Finite Mixture models. John Wiley & Sons, Inc., New York (2000)
Van Mierlo, H., Vermunt, J.K., Rutte, C.: Using individual level survey data to measure group constructs: A comparison of items with reference to the individual and to the group in a job design context (submitted for publication)
Vermunt, J.K.: Log-linear Models for Event Histories, QASS, vol. 8. Sage Publications, Thousand Oaks (1997)
Vermunt, J.K.: Multilevel latent class models, Sociological Methodology, 33 (to appear)
Vermunt, J.K.: The use restricted latent class models for defining and testing nonparametric and parametric IRT models. Applied Psychological Measurement 25, 283–294 (2001)
Vermunt, J.K., Magidson, J.: Latent GOLD 2.0 User’s Guide. Statistical Innovations Inc., Belmont (2000)
Vermunt, J.K., Magidson, J.: Addendum to the Latent GOLD User’s Guide: Upgrade Manual for Version 3.0. Statistical Innovations Inc., Belmont (2003)
Vermunt, J.K., Magidson, J.: Factor Analysis with Categorical Indicators: A Comparison Between Traditional and Latent Class Approaches. In: Van der Ark, A., Croon, M., Sijstma, K. (eds.) Advancements in Categorical Data Analysis. Erlbaum (to appear)
Vermunt, J.K., Van Dijk, L.: A nonparametric random-coefficients approach: the latent class regression model. Multilevel Modelling Newsletter 13, 6–13 (2001)
Wedel, M., DeSarbo, W.: Mixture regression models. In: Hagenaars, J., McCutcheon, A. (eds.) Applied Latent Class Analysis, pp. 366–382. Cambridge University Press, Cambridge (2002)
Zhang, N.L.: Hierarchical latent class models for cluster analysis. Journal of Machine Learning Research (to appear)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Vermunt, J.K. (2003). Applications of Latent Class Analysis in Social Science Research. In: Nielsen, T.D., Zhang, N.L. (eds) Symbolic and Quantitative Approaches to Reasoning with Uncertainty. ECSQARU 2003. Lecture Notes in Computer Science(), vol 2711. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45062-7_2
Download citation
DOI: https://doi.org/10.1007/978-3-540-45062-7_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40494-1
Online ISBN: 978-3-540-45062-7
eBook Packages: Springer Book Archive