## Search found 139 matches

Mon Apr 20, 2020 5:39 pm
Forum: MLwiN user forum
Topic: variance function and its uncertainty
Replies: 3
Views: 1923

### Re: variance function and its uncertainty

Hi Sun,
Not really as as you say you don't have normality so any use of the SEs would be very approximate. you might consider bootstrapping I guess but easiest with MCMC.
Best wishes,
Bill.
Thu Apr 02, 2020 3:33 pm
Forum: MLwiN user forum
Topic: variance function and its uncertainty
Replies: 3
Views: 1923

### Re: variance function and its uncertainty

Hi Sun, With regard MCMC my suggestion is to look at my MCMC manual where I cover how one works out confidence intervals for derived quantities - here I cover in section 4.7 the difference between 2 schools, 4.8 their ranks with CIs and most relevant for you the ICC/VPC in section 4.9. Here you can ...
Fri Mar 13, 2020 4:26 pm
Forum: runmlwin user forum
Topic: Jointly test coefficient is 0 across 3 outcomes from trivariate cross-classified model fitted using MCMC
Replies: 1
Views: 1333

### Re: Jointly test coefficient is 0 across 3 outcomes from trivariate cross-classified model fitted using MCMC

Hi Rachael,
MCMC is fitting a Bayesian model so the concept of a classical P value is not valid for MCMC estimates - I think we do offer Bayesian P values for all parameters though which basically check what proportion of iterations are positive / negative for a chain.
Best wishes,
Bill.
Thu Jan 23, 2020 3:07 pm
Forum: MLwiN user forum
Topic: Is level 2 variance significantly different from 0?
Replies: 1
Views: 1423

### Re: Is level 2 variance significantly different from 0?

That depends on which estimation method you are using but generally involves fitting the model with and without the random intercept and looking at some indicator of model fit - a LR test for ML methods or comparing DIC for MCMC. Suggest you look in the user guides for examples.
Bill.
Thu Jan 23, 2020 3:05 pm
Forum: runmlwin user forum
Topic: cross-classified MLM - MCM - random and fixed effects
Replies: 1
Views: 1415

### Re: cross-classified MLM - MCM - random and fixed effects

Hi Johann, Generally when we talk about cross-classified models we are assuming that each of these levels is a random source of variation and is treated as a set of RANDOM effects. It doesn't make a lot of sense to include fixed effects as well as random effects for the same terms. Generally fixed e...
Tue Nov 26, 2019 1:57 pm
Forum: runmlwin user forum
Topic: 95% prediction interval for new obs from same cluster populations
Replies: 3
Views: 2022

### Re: 95% prediction interval for new obs from same cluster populations

Hi Rachael,
Just generate a level 1 residual (using the level 1 variance) and add it to the prediction and you should be sorted.
Bill.
Tue Nov 26, 2019 12:40 pm
Forum: runmlwin user forum
Topic: 95% prediction interval for new obs from same cluster populations
Replies: 3
Views: 2022

### Re: 95% prediction interval for new obs from same cluster populations

Hi Rachael,
If you were hoping to get 95% intervals for individuals rather than for the average individual you will also need to have level 1 in your predictions I would expect.
Best wishes,
Bill.
Wed Aug 07, 2019 1:11 pm
Forum: MLwiN user forum
Topic: Wald test and SE of variances
Replies: 2
Views: 2466

### Re: Wald test and SE of variances

Hi Sun, the Wald test is only an approximate test for variance parameters as they do not have a normal distribution. That withstanding the test will form the difference of the 2 variances and then work out the SE for this difference to test for significance. This SE is made up of the SE for each par...
Mon Jul 15, 2019 9:29 am
Forum: MLwiN user forum
Topic: Higher level predictors: are they worth it?
Replies: 2
Views: 3189

### Re: Higher level predictors: are they worth it?

Dear John, I would say that it would be important to include the level 2 predictors. In some respect you are largely doing the multilevel modelling to control for variation in the response variable that can be explained by clustering into groups. Of course putting level 2 predictors into the model c...
Fri Jun 21, 2019 12:32 pm
Forum: runmlwin user forum
Topic: Interpretation of the Raftery-Lewis value
Replies: 2
Views: 4240

### Re: Interpretation of the Raftery-Lewis value

Hi Rach, Raftery and Lewis is a completely different diagnostic to the ESS and so works on actual iterations and so you need to run for 19,445 actual iterations to satisfy it. With regard ESS generally one looks for some criterion like > 500 for all parameters. The ESS works on correlations in the c...