Hello George,
Thank you very much for your very fast and helpful reply again.
As always, I highly appreciate your reply and the great variety of features in (run)mlwin! :)
I managed to estimate several equations simultaneously and am now facing a new problem.
It would be awesome if you could ...
Search found 6 matches
- Sun May 12, 2013 11:45 am
- Forum: runmlwin user forum
- Topic: Estimating multiple equations simultaneously
- Replies: 3
- Views: 6547
- Sun May 05, 2013 12:58 pm
- Forum: runmlwin user forum
- Topic: Estimating multiple equations simultaneously
- Replies: 3
- Views: 6547
Estimating multiple equations simultaneously
Hello everyone,
is it possible to use runmlwin to estimate multiple equations simultaneously?
1. Seemingly unrelated equations
I'd like to estimate a model that consists of several regression equations, each having its own dependent variable and potentially different sets of exogenous ...
is it possible to use runmlwin to estimate multiple equations simultaneously?
1. Seemingly unrelated equations
I'd like to estimate a model that consists of several regression equations, each having its own dependent variable and potentially different sets of exogenous ...
- Fri Mar 08, 2013 3:42 pm
- Forum: runmlwin user forum
- Topic: Predict random effects of interest
- Replies: 4
- Views: 7204
Re: Predict random effects of interest
Hi George,
Thank you so much for this fast and very helpful response!
It works perfectally!
I'd like to mention a little problem that I could solve on my own because others may find this helpful.
One of my clusters contains 15 agents (1-15). Initially, I got missing values for the predicted ...
Thank you so much for this fast and very helpful response!
It works perfectally!
I'd like to mention a little problem that I could solve on my own because others may find this helpful.
One of my clusters contains 15 agents (1-15). Initially, I got missing values for the predicted ...
- Thu Mar 07, 2013 9:31 pm
- Forum: runmlwin user forum
- Topic: Predict random effects of interest
- Replies: 4
- Views: 7204
Predict random effects of interest
Hello everybody,
I'm running a MCMC logit model with crossed random effects.
Is there a way to give out the particular random effect and to predict the effects as if I were using a fixed-effects approach?
I have groups of different people using random effects but would also like to get more ...
I'm running a MCMC logit model with crossed random effects.
Is there a way to give out the particular random effect and to predict the effects as if I were using a fixed-effects approach?
I have groups of different people using random effects but would also like to get more ...
- Wed Feb 20, 2013 8:45 am
- Forum: runmlwin user forum
- Topic: Using Stata commands lroc and lstat after runmlwin
- Replies: 6
- Views: 22817
Using Stata commands lroc and lstat after runmlwin
Hello everybody,
I'm running a multilevel logit model with crossed-random effects using runmlwin.
I would like to let Stata calculate the Area Under the ROC curve afterwards as explained here: http://www.ats.ucla.edu/stat/stata/faq/roc.htm
using the lroc, nograph command. Similiarly, there is a ...
I'm running a multilevel logit model with crossed-random effects using runmlwin.
I would like to let Stata calculate the Area Under the ROC curve afterwards as explained here: http://www.ats.ucla.edu/stat/stata/faq/roc.htm
using the lroc, nograph command. Similiarly, there is a ...
- Wed Dec 05, 2012 6:09 pm
- Forum: runmlwin user forum
- Topic: Constraints for cross-classification
- Replies: 1
- Views: 5289
Constraints for cross-classification
Hello,
I would like to fit a multilevel model with binary responses and a crossed effect.
My data is structured as follows: level1: approx. 800 loans, level2: 700 borrowers, level3: crossed effects because borrowers can be clustered by 15 agents or 20 regions.
I declare a fourth level, create ...
I would like to fit a multilevel model with binary responses and a crossed effect.
My data is structured as follows: level1: approx. 800 loans, level2: 700 borrowers, level3: crossed effects because borrowers can be clustered by 15 agents or 20 regions.
I declare a fourth level, create ...