Hi Marjolin,
Don't see any problem here - your variables appears to explain 2 thirds of the level 3 variation and the Z score is only 4.3 which although very significant you do have 6000 data points and so it is possible to have much bigger Z scores.
Best wishes,
Bill.
Search found 156 matches
- Fri Jun 02, 2017 9:23 am
- Forum: MLwiN user forum
- Topic: low unexplained variance on third level, but third level variable with high explanatory power
- Replies: 1
- Views: 3191
- Wed May 10, 2017 2:29 pm
- Forum: runmlwin user forum
- Topic: test for a difference in Bayesian DIC
- Replies: 2
- Views: 4190
Re: test for a difference in Bayesian DIC
Hi Zuzanna, The DIC is an information criterion like the AIC and BIC in classical statistics and basically such quantities do not have an underlying statistical distribution and so the concept of significance doesn't work for such measures. It is therefore just the case that rules of thumb are used ...
- Wed Apr 19, 2017 9:45 am
- Forum: MLwiN user forum
- Topic: Assumptions cross-classification models
- Replies: 1
- Views: 3306
Re: Assumptions cross-classification models
Hi Griet,
In theory a nested structure is a special case of the more general crossed-structure with no crossing !! So yes there is no restriction here and if you tried selecting cross-classified for a nested structure you should get the same answers.
Bill.
In theory a nested structure is a special case of the more general crossed-structure with no crossing !! So yes there is no restriction here and if you tried selecting cross-classified for a nested structure you should get the same answers.
Bill.
- Wed Mar 01, 2017 1:23 pm
- Forum: MLwiN user forum
- Topic: Classification order in cross-classified multilevel models
- Replies: 1
- Views: 3536
Re: Classification order in cross-classified multilevel models
Hi Griet, It shouldn't matter but (1) you should make sure you tick the cross-classified button so that it is fitting the XC model! (2) you should ensure you run the MCMC estimation for sufficiently long that the chains converge to similar answers - they will not be exactly the same due to the Monte...
- Fri Feb 10, 2017 9:58 am
- Forum: MLwiN user forum
- Topic: multilevel-analysis, predictor
- Replies: 4
- Views: 5453
Re: multilevel-analysis, predictor
Hi Ine, What you are proposing would be a false replication i.e. you will be pretending you have more data than you have (particularly if you didn't put in the level 2 random effect). In fact once you put the random effect in unsurprisingly it will show all the variance is at level 2 and might in so...
- Thu Jan 26, 2017 5:26 pm
- Forum: MLwiN user forum
- Topic: saving within-group residual variances
- Replies: 4
- Views: 5121
Re: saving within-group residual variances
Hi Nina,
Not sure I understand your question with regard the per group statement. The model will have a variance at level 1 and level 2 and residuals at level 2 but there isn't a different variance for each group in this model.
Best wishes,
Bill.
Not sure I understand your question with regard the per group statement. The model will have a variance at level 1 and level 2 and residuals at level 2 but there isn't a different variance for each group in this model.
Best wishes,
Bill.
- Fri Jan 13, 2017 10:10 am
- Forum: runmlwin user forum
- Topic: comparing models
- Replies: 2
- Views: 3709
Re: comparing models
Hi Marie,
To compare models 2 and 3 you can fit them both using runmlwin and MCMC and then compare the 2 DIC values.
Regards,
Bill.
To compare models 2 and 3 you can fit them both using runmlwin and MCMC and then compare the 2 DIC values.
Regards,
Bill.
- Fri Nov 25, 2016 4:30 pm
- Forum: MLwiN user forum
- Topic: Collapsing response categories on the basis of strong correlation between random effects
- Replies: 2
- Views: 5706
Re: Collapsing response categories on the basis of strong correlation between random effects
Hi Moletsane Monyake, It is perfectly acceptable to collapse ordered categories into smaller numbers of categories on practical grounds and as you say on ease of interpretation grounds. I wouldn't worry too much about things like residuals etc. which are often hard to interpret for ordered category ...
- Thu Nov 17, 2016 7:42 pm
- Forum: MLwiN user forum
- Topic: multi-level models with repeated measures
- Replies: 2
- Views: 7490
Re: multi-level models with repeated measures
Hi Stuart, Some thoughts. As you are looking at change and you only have 2 time points then I would have thought you would be considering the baseline as a predictor variable and the second time point as the response thus removing your time point level. As for your behaviours I would suggest that he...
- Tue Sep 20, 2016 12:07 pm
- Forum: MLwiN user forum
- Topic: effect sizes?
- Replies: 3
- Views: 9115
Re: effect sizes?
Hi jellie1410,
I guess your best bet is to look for examples where multilevel models have been used in the journal in question and copy the conventions used. Some journals simply have tables with coefficients, some with binary responses use odds ratios etc.
I guess your best bet is to look for examples where multilevel models have been used in the journal in question and copy the conventions used. Some journals simply have tables with coefficients, some with binary responses use odds ratios etc.