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?
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Fit for 2 latent classes:
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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
