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- W43163975 abstract "When latent class parameters are estimated, maximum likelihood and Pearson chi-square statistics can be derived for assessing the fit of the model to the data. This study uses simulated data to compare these two statistics. Data were generated for a 2-class unconstrained model and a 3-class constrained model. Data were also generated under three independent variables. Those variables are sample she and two parameters that define latent class models--conditional response probability and latent class proportion. Parameters were estimated for the generation models and a series of subsumed and subsuming models. Maximum likelihood and Pearson chi-square statistics were derived for each estimation. Distributions of fit statistics were prcduced by 1000 replications. For each distribution of statistics, the overall fit to tht appropriate chi-square distribution is assessed. In addition, the mean, variance, and tail weights are examined. The distributions of the statistics vary according to the parameter values of the models and the type of models estimated. When the estimated model is an accurate reflection of the data, the Pearson statistic is generally distributed as chi-square for both large and small samples, while the maximum likelihood statistic is distributed as chi-square only at the large sample" @default.
- W43163975 created "2016-06-24" @default.
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- W43163975 date "1988-01-01" @default.
- W43163975 modified "2023-09-27" @default.
- W43163975 title "Comparison of Maximum Likelihood and Pearson Chi-Square Statistics for Assessing Latent Class Models." @default.
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