By Jacques A. Hagenaars, Allan L. McCutcheon
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Extra resources for Applied Latent Class Analysis
We have commented in this section on each of the models in Tables 5a and 5b, except for model M2 . This model will be considered later in the Appendix. , models M1 , M3 , and M5 in Tables 6, 7, and 8, respectively). (2) When the observed relationships among the responses on the observed variables (A, B, C, D) are thought to be a consequence of having respondents who differ among themselves in some unobserved manner, the latent class model can be used to investigate the unobserved heterogeneity among the respondents, with each latent class viewed as a homogeneous category, and with the different latent classes 22 Leo A.
Also, with Figure 1(b) and/or Figure 1(c) we can explain the statistically significant relationship. , loglinear analysis, logit analysis). In the Appendix we further comment on the latent class analysis of Table 1. Latent Class Analysis 13 Table 3. Observed and Estimated Expected Frequencies under the H0 and H1 Models Estimated Expected Frequency Cross-Classiﬁcation Obs. 74 94 8 Goodness-of-ﬁt chi square Percentage reduction Degrees of freedom Note: The H0 model is the null model of independence; the H1 model is the two-class latent class model; these models are applied to the cross-classiﬁed data in Table 1.
In model M5 , 17% are estimated to be in the strictly universalistic latent class, 77% in the mixed universalistically/particularistically inclined class, and 5% in the strictly particularistic class. situations B and C, and also for situations A and D. We have here in Table 8 an explanation (or description) of the data in Table 4 that is very parsimonious indeed. We have commented in this section on each of the models in Tables 5a and 5b, except for model M2 . This model will be considered later in the Appendix.
Applied Latent Class Analysis by Jacques A. Hagenaars, Allan L. McCutcheon