are there any special concerns with this model. it seems to be using some sort of quadrature in the estimation and takes forever to converge. the code i used is below. any advice would be great. thanks.
================================= TITLE: Binary outcome on CFA DATA: FILE IS L:\data_mil_1_3a.dat; FORMAT IS free; TYPE IS individual; OUTPUT: STAND; VARIABLE: NAMES ARE mil hhinc medu fedu hhincx unempx; USEVARIABLES ARE mil hhinc medu fedu hhincx unempx; CATEGORICAL IS mil; MISSING ARE .; ANALYSIS: TYPE IS missing meanstructure; ESTIMATOR IS ML; MODEL: mil ON ses; ses BY hhinc medu fedu hhincx unempx;
This model requires numerical integration. I think it would be only one dimension so I don't know why it would be particularly slow. If you send the input, data, output, and your license number to firstname.lastname@example.org, I can look into it.
Quick question regarding a binary DV SEM model. I am running a logit SEM model with a binary DV and I noticed that there is no r-squared in the output. Is there any way of obtaining an r-squared or do I interrupt this using the odds ratios?
Yes. The first column is R-square. The second is its standard error. The third is the ratio of the estimate to its standard error which is a z-test in large samples. The p-value for this z-test is given in the last column.