A statistical question, semi-related to Mplus, maybe you can help. I am trying to do compute an LRT (loglikelihood ratio test) between two nested models using a multiply imputed data set. The model is logistic regression.
The type=imputation command line produces a mean loglikelihood with a standard deviation. How do I compute the LRT test from this accounting for the SE of the log likelihood? Can Mplus compute an LRT test between two or multiple nested models for me?
The latter questions is also more general - I would not know how to have Mplus perform an LRT it in a single data set case.
This article describes the LRT-imputation method of Meng and Rubin.
In Mplus this method is implemented for the test of model fit (unrestricted model v.s. structural model). For general pair of nested models the method is not yet implemented in Mplus. Alternatively you may be able to utilize the Wald test (see the above note for description) available with the "Model test" command.
Without imputations the LRT is is simply double the log-likelihood difference between the two nested models.