IDEAS home Printed from https://ideas.repec.org/p/iza/izadps/dp8283.html
   My bibliography  Save this paper

A New Formulation for Latent Class Models

Author

Listed:
  • Brown, Sarah

    (University of Sheffield)

  • Greene, William H.

    (University of South Florida)

  • Harris, Mark N.

    (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.

Suggested Citation

  • Brown, Sarah & Greene, William H. & Harris, Mark N., 2014. "A New Formulation for Latent Class Models," IZA Discussion Papers 8283, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp8283
    as

    Download full text from publisher

    File URL: https://docs.iza.org/dp8283.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Beth A. Reboussin & Edward H. Ip & Mark Wolfson, 2008. "Locally dependent latent class models with covariates: an application to under‐age drinking in the USA," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(4), pages 877-897, October.
    2. Terza, Joseph V. & Basu, Anirban & Rathouz, Paul J., 2008. "Two-stage residual inclusion estimation: Addressing endogeneity in health econometric modeling," Journal of Health Economics, Elsevier, vol. 27(3), pages 531-543, May.
    3. Deb, Partha & Trivedi, Pravin K., 2002. "The structure of demand for health care: latent class versus two-part models," Journal of Health Economics, Elsevier, vol. 21(4), pages 601-625, July.
    4. Chou, Shin-Yi & Grossman, Michael & Saffer, Henry, 2004. "An economic analysis of adult obesity: results from the Behavioral Risk Factor Surveillance System," Journal of Health Economics, Elsevier, vol. 23(3), pages 565-587, May.
    5. Brown, Heather & Roberts, Jennifer, 2013. "Born to be wide? Exploring correlations in mother and adolescent body mass index," Economics Letters, Elsevier, vol. 120(3), pages 413-415.
    6. Bago d'Uva, Teresa & Jones, Andrew M., 2009. "Health care utilisation in Europe: New evidence from the ECHP," Journal of Health Economics, Elsevier, vol. 28(2), pages 265-279, March.
    7. David M. Cutler & Edward L. Glaeser & Jesse M. Shapiro, 2003. "Why Have Americans Become More Obese?," Journal of Economic Perspectives, American Economic Association, vol. 17(3), pages 93-118, Summer.
    8. Fry, Tim R. L. & Harris, Mark N., 1996. "A Monte Carlo study of tests for the independence of irrelevant alternatives property," Transportation Research Part B: Methodological, Elsevier, vol. 30(1), pages 19-30, February.
    9. Yang, Hongxia & O’Brien, Sean & Dunson, David B., 2011. "Nonparametric Bayes Stochastically Ordered Latent Class Models," Journal of the American Statistical Association, American Statistical Association, vol. 106(495), pages 807-817.
    10. Hamparsum Bozdogan, 1987. "Model selection and Akaike's Information Criterion (AIC): The general theory and its analytical extensions," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 345-370, September.
    11. Junyi Shen, 2009. "Latent class model or mixed logit model? A comparison by transport mode choice data," Applied Economics, Taylor & Francis Journals, vol. 41(22), pages 2915-2924.
    12. Greene,William H. & Hensher,David A., 2010. "Modeling Ordered Choices," Cambridge Books, Cambridge University Press, number 9780521194204, January.
    13. Greene, William & Harris, Mark N. & Hollingsworth, Bruce & Maitra, Pushkar, 2014. "A latent class model for obesity," Economics Letters, Elsevier, vol. 123(1), pages 1-5.
    14. Hwan Chung & James C. Anthony & Joseph L. Schafer, 2011. "Latent class profile analysis: an application to stage sequential processes in early onset drinking behaviours," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 174(3), pages 689-712, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Burnett, J. Wesley, 2016. "Club convergence and clustering of U.S. energy-related CO2 emissions," Resource and Energy Economics, Elsevier, vol. 46(C), pages 62-84.
    2. Max Nathan, 2016. "Ethnic diversity and business performance: Which firms? Which cities?," Environment and Planning A, , vol. 48(12), pages 2462-2483, December.
    3. Brown, Sarah & Durand, Robert B. & Harris, Mark N. & Weterings, Tim, 2014. "Modelling financial satisfaction across life stages: A latent class approach," Journal of Economic Psychology, Elsevier, vol. 45(C), pages 117-127.
    4. Nathan, Max, 2014. "Top Team Diversity and Business Performance: Latent Class Analysis for Firms and Cities," IZA Discussion Papers 8462, Institute of Labor Economics (IZA).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sarah Brown & William Greene & Mark Harris, 2020. "A novel approach to latent class modelling: identifying the various types of body mass index individuals," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(3), pages 983-1004, June.
    2. Brown, Sarah & Greene, William H. & Harris, Mark N. & Taylor, Karl, 2015. "An inverse hyperbolic sine heteroskedastic latent class panel tobit model: An application to modelling charitable donations," Economic Modelling, Elsevier, vol. 50(C), pages 228-236.
    3. Sarrias, Mauricio, 2021. "A two recursive equation model to correct for endogeneity in latent class binary probit models," Journal of choice modelling, Elsevier, vol. 40(C).
    4. Nadja Kairies-Schwarz & Johanna Kokot & Markus Vomhof & Jens Wessling, 2014. "How Do Consumers Choose Health Insurance? – An Experiment on Heterogeneity in Attribute Tastes and Risk Preferences," Ruhr Economic Papers 0537, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.
    5. Courtemanche, Charles & Tchernis, Rusty & Ukert, Benjamin, 2018. "The effect of smoking on obesity: Evidence from a randomized trial," Journal of Health Economics, Elsevier, vol. 57(C), pages 31-44.
    6. sarah Brown & Mark N Harris & Karl Taylor, 2010. "Modelling Charitable Donations: A Latent Class Panel Approach," Working Papers 2010017, The University of Sheffield, Department of Economics, revised Sep 2010.
    7. Raslan Alzuabi & Sarah Brown & Mark N. Harris & Karl Taylor, 2024. "Modelling the composition of household portfolios: A latent class approach," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 57(1), pages 243-275, February.
    8. Hendrik Schmitz, 2012. "More health care utilization with more insurance coverage? Evidence from a latent class model with German data," Applied Economics, Taylor & Francis Journals, vol. 44(34), pages 4455-4468, December.
    9. repec:zbw:rwirep:0537 is not listed on IDEAS
    10. Kairies-Schwarz, Nadja & Kokot, Johanna & Vomhof, Markus & Wessling, Jens, 2014. "How Do Consumers Choose Health Insurance? – An Experiment on Heterogeneity in Attribute Tastes and Risk Preferences," Ruhr Economic Papers 537, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    11. Durand, Robert B. & Greene, William H. & Harris, Mark N. & Khoo, Joye, 2022. "Heterogeneity in speed of adjustment using finite mixture models," Economic Modelling, Elsevier, vol. 107(C).
    12. Dunn, Richard A. & Sharkey, Joseph R. & Horel, Scott, 2012. "The effect of fast-food availability on fast-food consumption and obesity among rural residents: An analysis by race/ethnicity," Economics & Human Biology, Elsevier, vol. 10(1), pages 1-13.
    13. Paolo Li Donni & Ranjeeta Thomas, 2020. "Latent class models for multiple ordered categorical health data: testing violation of the local independence assumption," Empirical Economics, Springer, vol. 59(4), pages 1903-1931, October.
    14. Anura Amarasinghe & Gerard D'Souza & Cheryl Brown & Tatiana Borisova, 2006. "A Spatial Analysis of Obesity in West Virginia," Working Papers Working Paper 2006-13, Regional Research Institute, West Virginia University.
    15. John Komlos, 2009. "Recent Trends in Height by Gender and Ethnicity in the US in Relation to Levels of Income," NBER Working Papers 14635, National Bureau of Economic Research, Inc.
    16. Chouinard, Hayley H & Davis, David E. & LaFrance, Jeffrey T. & Perloff, Jeffrey M, 2005. "The Effects of a Fat Tax on Dairy Products," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt60t1f3tn, Department of Agricultural & Resource Economics, UC Berkeley.
    17. William H. Greene & Mark N. Harris & Rachel J. Knott & Nigel Rice, 2021. "Specification and testing of hierarchical ordered response models with anchoring vignettes," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(1), pages 31-64, January.
    18. Euna Han & Lisa M. Powell, 2013. "Fast Food Prices And Adult Body Weight Outcomes: Evidence Based On Longitudinal Quantile Regression Models," Contemporary Economic Policy, Western Economic Association International, vol. 31(3), pages 528-536, July.
    19. Trenton Smith, 2009. "Reconciling psychology with economics: Obesity, behavioral biology, and rational overeating," Journal of Bioeconomics, Springer, vol. 11(3), pages 249-282, December.
    20. Costa-Font, Joan & Fabbri, Daniele & Gil, Joan, 2009. "Decomposing body mass index gaps between Mediterranean countries: A counterfactual quantile regression analysis," Economics & Human Biology, Elsevier, vol. 7(3), pages 351-365, December.
    21. Giampiero Marra & Matteo Fasiolo & Rosalba Radice & Rainer Winkelmann, 2023. "A flexible copula regression model with Bernoulli and Tweedie margins for estimating the effect of spending on mental health," Health Economics, John Wiley & Sons, Ltd., vol. 32(6), pages 1305-1322, June.

    More about this item

    Keywords

    latent class models; finite mixture models; ordered probability models; expected values; body mass index;
    All these keywords.

    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • D1 - Microeconomics - - Household Behavior
    • I1 - Health, Education, and Welfare - - Health

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:iza:izadps:dp8283. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Holger Hinte (email available below). General contact details of provider: https://edirc.repec.org/data/izaaade.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.