Dear all, I have just sent a message asking about poLCA but I thought of another question I wanted to ask. I get the G^2 statistic in my output and want to test for its significance. I get that the degrees of freedom for the test are (S-1-p) where S is the number of different patterns observed and p is the number of estimated parameters. Are these the "residual degrees of freedom" that I get in the output?
========================================================= Fit for 2 latent classes: ========================================================= number of observations: 1559 number of estimated parameters: 25 residual degrees of freedom: 1534 maximum log-likelihood: -7419.601 AIC(2): 14889.20 BIC(2): 15023.00 G^2(2): 1088.866 (Likelihood ratio/deviance statistic) X^2(2): 2284.071 (Chi-square goodness of fit) ========================================================= If I use these degrees of freedom for the test I get really high probabilities for the model even with only 2 classes. Am I doing something wrong? If these are not the degrees of freedom for the test is there any way to calculate them (i.e.: finding the S to substitute in the S-1-p formula)? Kind regards Guilherme Kenji ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
