Search found 25 matches

by johannesmueller
Mon Apr 01, 2019 2:07 pm
Forum: runmlwin user forum
Topic: Cross-classified logit model: Getting the ICCs
Replies: 8
Views: 26523

Re: Cross-classified logit model: Getting the ICCs

Thank you so much for all your help, Bill, absolutely fantastic and highly appreciated!
Have a great week,
Johannes
by johannesmueller
Sun Mar 31, 2019 11:44 am
Forum: runmlwin user forum
Topic: Cross-classified logit model: Getting the ICCs
Replies: 8
Views: 26523

Re: Cross-classified logit model: Getting the ICCs

Dear Bill,

Thank you so much for getting back to me.
This sounds great.
Just to be 100% sure: This should get me to my goal of having the ICCs from an additive cross-classified model, correct?
In the null-model, the ICCs and VPC are identical, or is there some adjustment that'd be needed to also ...
by johannesmueller
Fri Mar 29, 2019 11:43 am
Forum: runmlwin user forum
Topic: Cross-classified logit model: Getting the ICCs
Replies: 8
Views: 26523

Re: Cross-classified logit model: Getting the ICCs

Hi Bill,

Thank you very much for your reply and the suggestion. To be honest, I have appreciated you article a lot but it also is a bit beyond my current involvement with methodology; I am inherently an applied researcher with its pros and cons...

Hence, I was wondering whether you could possibly ...
by johannesmueller
Fri Oct 12, 2018 7:11 pm
Forum: runmlwin user forum
Topic: Cross-classified logit model: Getting the ICCs
Replies: 8
Views: 26523

Cross-classified logit model: Getting the ICCs

Dear all,

I am trying the calculate the ICCs of a cross-classified logit model where I have three non-hierarchically nested random terms. I can find the information how to do so for a two-level logit, and for more complex cross-classified models with a normally distributed dependent variable, but I ...
by johannesmueller
Sun Jul 29, 2018 12:46 pm
Forum: runmlwin user forum
Topic: cross-classified/cross-nested model: How to get all relevant random components
Replies: 1
Views: 9617

cross-classified/cross-nested model: How to get all relevant random components

Dear Madam or Sir,

I am running a cross-classified / cross-nested model in runmlwin and have some issues with the cross-classification for which I am seeking your help:


runmlwin DV cons, level4(year: cons) level3(Geo1: cons) level2(Geo2: cons) level1(ID: cons) mcmc(cc) initsb(b) nopause ...