2006
DOI: 10.1016/j.csda.2004.11.004
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Evaluating latent class analysis models in qualitative phenotype identification

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Cited by 474 publications
(360 citation statements)
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“…Nested models were compared to determine the number of classes that provided the best model fit. The fit of models was compared by the bootstrap of the Lo-MendellRubin Likelihood Ratio Test (Lo et al, 2001), the Bayesian Information Criterion (BIC; Yang, 2006) and entropy. Class membership was decided based on the (maximum) probability of membership in each class.…”
Section: Discussionmentioning
confidence: 99%
“…Nested models were compared to determine the number of classes that provided the best model fit. The fit of models was compared by the bootstrap of the Lo-MendellRubin Likelihood Ratio Test (Lo et al, 2001), the Bayesian Information Criterion (BIC; Yang, 2006) and entropy. Class membership was decided based on the (maximum) probability of membership in each class.…”
Section: Discussionmentioning
confidence: 99%
“…Different criteria were used to determine the best model (Nylund et al, 2007). First, the Bayesian Information Criterion (BIC; Henson, Reise, & Kim, 2007) and the sample-size adjusted BIC (SSA-BIC; Yang, 2006) were inspected, with lower values indicating better model fit. Second, the bootstrap likelihood ratio test (BLRT; Nylund et al, 2007) was used to compare the fit of two competing models.…”
Section: Discussionmentioning
confidence: 99%
“…The best-fit fourclass solution selected for each offending stage presented high classification accuracy based on posterior probabilities 5 , confirming their stability and relevance. The assigned label and probability of membership for each encounter site and victim release site class, as well as the item-response probabilities for endorsing each item of the class, are shown in Tables 3 and 4 tends to underestimate the number of latent classes when limited sample sizes and/or large numbers of parameters are engaged (Yang, 2006). 5 Average assignment probabilities based on posterior probabilities for the four model solution ranged from .973 (.564-.993; neighborhood site profile), to .912 (.413-.999; shopping center site profile) for the victim encounter LCA solution and from .999 (.999-1.00; unfamiliar site profile), to .940 (.536-1.00; shopping center site profile) for the victim release LCA solution.…”
Section: Identification Of Latent Subgroups Of Victim Encounter and Vmentioning
confidence: 99%