Choosing the right modeling technique available in STATA

[Sam McCaw]

Dear Stata Experts:

I am working on an assignment to predict state policy on a particular issue. The assignment is more to predict state policy rather than find causal relationships between x and y.

My policy outcome variable has 5 choices, coded from 0 - 4. I am using 0 as the base outcome. I have 10 years of panel data but many of the variables change very slowly over time.

My initial hunch were to use the following models:

1) multinomial logit - since this is not a panel estimator I would have to limit this to a cross-sectional model with only 50 states which I think would be a problem. I am not sure if I can use the panel data as a "pooled" data without significant problems. Grateful for any advice on this.

Also, I was planning on using state and year dummies if I was able to use panel data.

2) xtologit: I could also use the random effects model. I could potentially argue that the outcomes are ordered but I was hoping to avoid this assumption.

3) gesem, mlogit: I am learning about this program right now and it seems promising. Does this seem like an appropriate option? Also, does gsem with mlogit allow me to predict outcome probabilities?

4) I was also advised to look into mixed methods. Any suggestions?

Grateful for any insight on the different choices I have.

Thanks.

SAM

[Nick Cox]

Please see #4 in https://www.statalist.org/forums/help#adviceextras which details our policy on homework, namely assignments that will be graded.

[Nick Cox]

The reply was meant for anyone reading the thread. If your assignment will be graded, asking for support goes beyond Statalist recommendations. I shouldn’t need to expand on this, as it is already explained in the link given.

[Nick Cox]

You chose the word assignment, not me. You should see how it can be misunderstood. So, your question is wide open to anyone who wants to reply.

[Nick Cox]

Please follow the OP’s duplicate thread if interested.