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      Auxiliary Variables in Mixture Modeling: Three-Step Approaches Using Mplus

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      Publication date Created:
      Publication date (Print):
      Journal: Structural Equation Modeling: A Multidisciplinary Journal
      Publisher: Informa UK Limited

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          Latent Class Modeling with Covariates: Two Improved Three-Step Approaches

          J. Vermunt (2010)
          Article 0 comments Cited 432 times – based on 0 reviews     Review now
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            Estimating Latent Structure Models with Categorical Variables: One-Step Versus Three-Step Estimators

            Annabel Bolck, Marcel Croon, Jacques Hagenaars (2004)
            We study the properties of a three-step approach to estimating the parameters of a latent structure model for categorical data and propose a simple correction for a common source of bias. Such models have a measurement part (essentially the latent class model) and a structural (causal) part (essentially a system of logit equations). In the three-step approach, a stand-alone measurement model is first defined and its parameters are estimated. Individual predicted scores on the latent variables are then computed from the parameter estimates of the measurement model and the individual observed scoring patterns on the indicators. Finally, these predicted scores are used in the causal part and treated as observed variables. We show that such a naive use of predicted latent scores cannot be recommended since it leads to a systematic underestimation of the strength of the association among the variables in the structural part of the models. However, a simple correction procedure can eliminate this systematic bias. This approach is illustrated on simulated and real data. A method that uses multiple imputation to account for the fact that the predicted latent variables are random variables can produce standard errors for the parameters in the structural part of the model.
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              Finite Mixture Modeling with Mixture Outcomes Using the EM Algorithm

              Bengt Muthén, Kerby Shedden (1999)
              Article 0 comments Cited 221 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                Title: Structural Equation Modeling: A Multidisciplinary Journal
                Abbreviated Title: Structural Equation Modeling: A Multidisciplinary Journal
                Publisher: Informa UK Limited
                ISSN (Print): 1070-5511
                ISSN (Electronic): 1532-8007
                Publication date Created: June 09 2014
                Publication date (Print): June 09 2014
                Volume: 21
                Issue: 3
                Pages: 329-341
                Article
                DOI: 10.1080/10705511.2014.915181
                SO-VID: 6ee75a33-649b-4b8b-a8e6-1dcee10f4ce5
                Copyright © © 2014
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