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• W2024353935 abstract "• This research evaluates the identification of latent classes in social networks. • For the historical network studied, the model identification is consistent with the original study. • A new Bayesian model comparison method is used to determine the number of latent classes. • This is based on the posterior distributions of the competing model deviances and of their class membership probabilities. • This finds that two classes are sufficient. This research evaluates the identification of group structure in social networks through the latent class model and a new Bayesian model comparison method for the number of latent classes. The approach is applied to a well-known network of women in Natchez Mississippi. The latent class analysis reproduces the group structure of the women identified by the original sociologists." @default.
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• W2024353935 date "2014-07-01" @default.
• W2024353935 modified "2023-09-23" @default.
• W2024353935 title "Statistical modelling of the group structure of social networks" @default.
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• W2024353935 doi "https://doi.org/10.1016/j.socnet.2014.03.002" @default.
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