Search found 111 matches

by billb
Wed Jul 18, 2012 2:39 pm
Forum: MLwiN user forum
Topic: Variance disappearing in shift from 2- to 3-level model
Replies: 4
Views: 3059

Re: Variance disappearing in shift from 2- to 3-level model

Hi Matt, I am still a little puzzled. If as you say there are 13 categories for each GOR then a nested 3 level model should have 12 level 3 with 12*13 categories = 156 level 2 units. The only way that categories should be 13 would be if you had a cross-classified model. Am happy to take a look if yo...
by billb
Thu Jun 28, 2012 2:23 pm
Forum: MLwiN user forum
Topic: Variance disappearing in shift from 2- to 3-level model
Replies: 4
Views: 3059

Re: Variance disappearing in shift from 2- to 3-level model

Hi Mattoftheday, your email puzzles me a little. When you say you have a structure of 12 > 13 > 84 do you in fact mean 12 GORS with 12*13 Categories within the 12 i.e. categories within GOR or do you mean you have a cross-classified structure with GOR crossed by Category ? Either way these sorts of ...
by billb
Mon May 21, 2012 8:50 am
Forum: MLwiN user forum
Topic: one-tailed test for a predictor in MCMC
Replies: 2
Views: 4153

Re: one-tailed test for a predictor in MCMC

Hi Sian, I think you are a little confused here. The DIC diagnostic is an information criterion that can be used to compare models in a similar way to the AIC and BIC in a non-Bayesian/MCMC setting. What it is not is equivalent to 'a two-tailed test at 5% significance level'. The closest thing in th...
by billb
Mon May 21, 2012 8:42 am
Forum: MLwiN user forum
Topic: question about a cross-classified model
Replies: 2
Views: 2760

Re: question about a cross-classified model

Hi Jelle, Yes this sounds appropriate for the analysis you intend to do. I would firstly look at each of the 2 ratings separately and fit a straightforward single response cross-classified model as in the chapter in my MCMC book. To fit a MV model you will need to follow the example in the MV Normal...
by billb
Mon Aug 15, 2011 1:23 pm
Forum: MLwiN user forum
Topic: Cross-classified multinomial problems
Replies: 2
Views: 4017

Re: Cross-classified multinomial problems

This shouldn't be too bad in MCMC. Basically set up your model as in the MCMC manual chapter for multinomial then add on the extra levels as you would anyway. Ignore any error messages from IGLS. Switch to MCMC and tick the cross classified box as in the cross classified chapter in the MCMC manual. ...
by billb
Mon Aug 15, 2011 1:20 pm
Forum: MLwiN user forum
Topic: Error 1909 using MCMC on Multivariate data
Replies: 1
Views: 2414

Re: Error 1909 using MCMC on Multivariate data

Hi Thomasm, If you wish to create imputed datasets to fill in what will ultimately be X variables in your model to fit you need to have them as response variables in the imputation model you first fit. Say for example with the hungary dataset your final model is going to be a regression of biol_core...
by billb
Mon Aug 15, 2011 1:11 pm
Forum: MLwiN user forum
Topic: CIs for slope residuals
Replies: 1
Views: 1901

Re: CIs for slope residuals

Hi Dave, I took a look at your data and discovered that the IGLS algorithm is estimating a non-positive definite variance matrix at level 2. Apologies for the technical jargon but basically if you were to look at your estimates for the between TherID variance matrix in the Estimate Tables window and...
by billb
Tue Aug 03, 2010 3:02 pm
Forum: MLwiN user forum
Topic: Residuals in MCMC
Replies: 1
Views: 2049

Re: Residuals in MCMC

Hi Michael,
Rather impressively you are the first person to spot this mistake - yes the elements given give 90% not 95% confidence intervals. If/When I get around to updating the manual next I'll try and amend this.
Thanks,
Bill.
by billb
Fri May 21, 2010 1:54 pm
Forum: MLwiN user forum
Topic: MCMC Error in CAR modelling
Replies: 1
Views: 2390

Re: MCMC Error in CAR modelling

Hi Karen,
I could take a look if you were happy to send on the worksheet. Note i and j might refer to the areas in the order the software receives them and not the labels they have.
Bill.
by billb
Fri May 21, 2010 1:51 pm
Forum: MLwiN user forum
Topic: Bizarre error message
Replies: 2
Views: 2952

Re: Bizarre error message

Hi NtD71, I suspect what happened is you had a column called 'P' in the data you imported and the macros for multinomial models name certain columns with single letter names including 'P'. Thus when the macro tries to name something as 'P' MLwiN complains that 'P' already exists. The only solution i...