Search found 12 matches

by mlwinnewbie
Mon Jul 07, 2014 9:17 am
Forum: runmlwin user forum
Topic: Wald test following multinomial logistic regression
Replies: 7
Views: 11179

Re: Wald test following multinomial logistic regression

Hi George,

Thanks a lot for your reply! Can I also double-check what you mean by "You can always manipulate the parameter estimates to get different log-odds contrasts if they are of interest" - how could I achieve that?

Thanks again,
Francesca
by mlwinnewbie
Fri Jul 04, 2014 3:32 pm
Forum: runmlwin user forum
Topic: Wald test following multinomial logistic regression
Replies: 7
Views: 11179

Re: Wald test following multinomial logistic regression

Hi George,

Thanks again for your helpful reply. I used the mcmc approach you suggested -

set more off
runmlwin invw topic2 topic3 cons, ///
level2(IDD: cons) ///
level1(id) ///
discrete(distribution(multinomial) ///
link(mlogit) ///
denominator(cons) ///
basecategory(2)) ///
nopause
estimates ...
by mlwinnewbie
Fri Jul 04, 2014 1:46 pm
Forum: runmlwin user forum
Topic: Wald test following multinomial logistic regression
Replies: 7
Views: 11179

Re: Wald test following multinomial logistic regression

Hi George,

Thank you very much for your reply - it is really helpful.

I was hoping you could comment on my second query - apologies if this is a very basic question:
Depending on the basecategory I select the overall Wald test produces different results - this is not the case when I use mlogit ...
by mlwinnewbie
Wed Jul 02, 2014 1:41 pm
Forum: runmlwin user forum
Topic: Wald test following multinomial logistic regression
Replies: 7
Views: 11179

Wald test following multinomial logistic regression

Hi everyone,

I am interested in assessing whether the topic selected (social vs. personal vs. clinical) is a predictor of involvement in therapy (yes, medium and low).

I wrote the following script in Stata:

global MLwiN_path "C:\Program Files (x86)\MLwiN v2.29\i386\mlwin.exe"
capture drop cons ...
by mlwinnewbie
Mon May 12, 2014 2:59 pm
Forum: runmlwin user forum
Topic: may not label .1666666716 error message
Replies: 4
Views: 5927

Re: may not label .1666666716 error message

Hi Chris,

Thanks a lot for your quick reply and apologies for such a silly mistake!

Fran
by mlwinnewbie
Mon May 12, 2014 2:35 pm
Forum: runmlwin user forum
Topic: may not label .1666666716 error message
Replies: 4
Views: 5927

Re: may not label .1666666716 error message

Hi thanks for your reply.

Below are some of the lines prior to the error message - I could not upload the log unfortunately. Let me know if you need to see more of the code.


---------------------------------------------------------------------------------------------------- begin label ...
by mlwinnewbie
Mon May 12, 2014 10:09 am
Forum: runmlwin user forum
Topic: may not label .1666666716 error message
Replies: 4
Views: 5927

may not label .1666666716 error message

Hi listers,

I am having problems running the runmlwin command for an mlogit regression. My DV (satisfaction) has 3 levels (yes, partly and no) and my IV also has 3 levels which code the kind of goal selected by the respondent (treatment, social or financial). I am interested to see if the type of ...
by mlwinnewbie
Thu May 01, 2014 7:53 am
Forum: runmlwin user forum
Topic: runmlwin with imputed data
Replies: 24
Views: 40805

Re: runmlwin with imputed data

Brilliant - thank you very much!
by mlwinnewbie
Wed Apr 30, 2014 3:18 pm
Forum: runmlwin user forum
Topic: runmlwin with imputed data
Replies: 24
Views: 40805

Re: runmlwin with imputed data

hi George,

I had a close look at your example dataset and script and realised what is causing the problem in my dataset. In your example the student ID codes (level 1) go from 1 to n for each school (level 2) whereas my ID codes go from 1 to 500 counting the overall sample rather than for each ...
by mlwinnewbie
Wed Apr 30, 2014 12:52 pm
Forum: runmlwin user forum
Topic: runmlwin with imputed data
Replies: 24
Views: 40805

Re: runmlwin with imputed data

Thanks again for your reply - I will have a play with your code and apply it to my data.

Thanks again!