By Allan L. McCutcheon
Latent category research is a robust device for reading the constitution of relationships between categorically scored variables. It allows researchers to discover the suitability of mixing or extra specific variables into typologies or scales. It additionally offers a mode for trying out hypotheses concerning the latent constitution between specific variables.
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Extra info for Latent Class Analysis (Quantitative Applications in the Social Sciences, 64)
Hagenaars, Social Sciences, Tilburg University Sally Jackson, Communications, University of Arizona Richard M. Jaeger, Education, University of North Carolina, Greensboro Gary King, Department of Government, Harvard University Roger E. Kirk, Psychology, Baylor University Helena Chmura Kraemer, Psychiatry and Behavioral Sciences, Stanford University Peter Marsden, Sociology, Harvard University Helmut Norpoth, Political Science, SUNY, Stony Brook Frank L. Schmidt, Management and Organization, University of Iowa Herbert Weisberg, Political Science, The Ohio State University Publisher Sara Miller McCune, Sage Publications, Inc.
17 can be used to test the fit of the obtained estimates to the originally observed data. There are three points that need to be made regarding the estimation of conditional and latent class probabilities. First, there might be more than one solution to the likelihood equations; that is, there may exist more than one set of conditional and latent class probabilities for any specified number of T latent classes. In other words, the maximum likelihood estimates may represent a local, rather than the global, maximum.
The identification problem). 25 are positive but for which no set of unique model parameters exist. 25 are positive (df = 1) but the model is not identified (Goodman 1974a). A necessary and sufficient condition for determining the local identifiability of a latent-class model is also provided by Goodman (1974a). 1). 1 must be of full column rank, equal to (I + J + K 2)T 1. In other words, there must be no linearly dependent columns. Calculation of the rank of this matrix is performed by the MLLSA program and is reported along with the parameter estimates.