Hello,

QUESTION 1 (test output): I am seeking advice on how to interpret potentially contradictory results from -oparallel- and -brant- tests. I'm trying to determine if I should run an -ologit- or -gologit- model.

I am predicting postsecondary enrollment (p2status) based on foreign-born students' school level (schaaa) when they arrived in the US relative to US-born peers, where 1= US-born (reference), 2= elementary age at arrival, 3= middle school age at arrival, 4=high school age at arrival.

BRANT TEST: If I am interpreting correctly (please see attachment with Stata output), the -brant- test indicates that the parallel regression assumption is violated in level 1 of the schaaa variable because it is significant, which means I should use a -gologit- model

OPARALLEL TEST: If I am interpreting correctly, none of the test statistics are significant, suggesting I should use the -ologit- model

Can someone please help me understand if I am misinterpreting my output? How do I determine if I should use the -ologit- or -gologit- model?



QUESTION 2 (error messages): when I run the full -ologit- model with all controls and then the -brant- test, I get an error saying "not all independent variables can be retained in binary logins; brant test cannot be computed" but I am not sure what this means.

Also, when I run the same full -ologit- model and then run the -oparallel- test, I get another error saying, "full model cannot be estimated due to perfect prediction" but I am also not sure what this means.

Any suggestions on what I should do to be able to run the -oparallel- and -brant- tests on my full model?


Thank you,
Irina

P.S. I am not super Stata literate, so if you can be generously detailed in your suggested steps, I would be very grateful