Simply add an extra level i.e. to fit a 3 level multivariate model in MLwiN one simply asks for 4 levels with the additional lowest level being used to represent the responses within an individual. Hope that helps.
Bill.
Search found 156 matches
- Wed May 20, 2015 8:31 am
- Forum: MLwiN user forum
- Topic: Three -level Multiple Imputation
- Replies: 4
- Views: 6844
- Thu Dec 18, 2014 10:39 am
- Forum: MLwiN user forum
- Topic: Multiple membership model with repeated measures
- Replies: 3
- Views: 5479
Re: Multiple membership model with repeated measures
Hi GijsHuitsing, But the issue here is there is a 1-1 mapping of outcomes to classes so probably no need to use multiple membership unless you are going to included some sort of cumulative effects for earlier class-rooms. One uses a multiple membership model if say you only had response at wave 3 bu...
- Tue Dec 02, 2014 9:07 am
- Forum: MLwiN user forum
- Topic: Multiple membership model with repeated measures
- Replies: 3
- Views: 5479
Re: Multiple membership model with repeated measures
Hi GijsHuitsing, I am unclear whether you have multiple membership or simply cross-classification? If your structure is that each measurement is nested within 1 student and 1 class but the classes change for measures then this is simply a cross-classification and you simply tick the cross-classified...
- Wed Nov 19, 2014 12:00 pm
- Forum: MLwiN user forum
- Topic: large data with cross-classified structure using MCMC
- Replies: 2
- Views: 4386
Re: large data with cross-classified structure using MCMC
Dear Xinyuzou, There are many reasons why mixing might be poor and different methods e.g. orthogonal parameterisation and hierarchical centering will fix different issues. Other things to consider are centering predictor variables. It may end up that you have to run for longer. The paper by Browne e...
- Fri Oct 17, 2014 4:01 pm
- Forum: MLwiN user forum
- Topic: variance of the linear predictor
- Replies: 4
- Views: 8009
Re: variance of the linear predictor
Hi Shane,
My immediate advice is to contact Joop directly as he may have a macro to do this in MLwiN which he has been known to use. Without reading Joop's book which I don't have time to as we speak I can't help you any further.
Apologies,
Bill.
My immediate advice is to contact Joop directly as he may have a macro to do this in MLwiN which he has been known to use. Without reading Joop's book which I don't have time to as we speak I can't help you any further.
Apologies,
Bill.
- Thu Aug 28, 2014 12:12 pm
- Forum: MLwiN user forum
- Topic: partial clustering at an intermediate level
- Replies: 1
- Views: 3969
Re: partial clustering at an intermediate level
HI Shane, It looks like in MQL1 that although a household variance is picked up it has a very large standard error which might suggest uncertainty that there are really significant household effects. I would suggest checking that your hierarchy is correct i.e. that the data is sorted correctly. I wo...
- Tue Jul 15, 2014 1:17 pm
- Forum: MLwiN user forum
- Topic: MLM in MLwiN with Censored Data
- Replies: 3
- Views: 6405
Re: MLM in MLwiN with Censored Data
Dear Edward, Apologies for the delay in replying - I think this might be a case of 'all models are wrong but some models are interesting' as George Box is quoted. Your normalised scores plot does indeed show something of an S shape which I am guessing is indicating the threshold at the top end. Of c...
- Wed Jul 02, 2014 4:08 pm
- Forum: MLwiN user forum
- Topic: MLM in MLwiN with Censored Data
- Replies: 3
- Views: 6405
Re: MLM in MLwiN with Censored Data
Hi Edward, MLwiN does not have specific functionality for handling censored data. In fact the exam datasets that are often used in educational examples have similar issues of censoring - where marks are assumed normally distributed but in reality are constrained to lie between 0 marks and full marks...
- Wed Jul 02, 2014 4:00 pm
- Forum: MLwiN user forum
- Topic: Higher level variation in Logistic multilevel regression
- Replies: 2
- Views: 4574
Re: Higher level variation in Logistic multilevel regression
Hi Frank, The level 2 variation in a binary response model is on a different scale (the logistic scale) from the response (the probability scale) and it is well known that when one adds predictors to a model this can have the effect of rescaling parameters so that the underlying binomial assumption ...
- Fri Jun 20, 2014 1:06 pm
- Forum: MLwiN user forum
- Topic: post hoc power calculation question
- Replies: 3
- Views: 15844
Re: post hoc power calculation question
Hi Sasso, Post-hoc power calculations are generally frowned upon in the stats community - see for example http://research-repository.st-andrews.ac.uk/bitstream/10023/679/5/Thomas-Retrospectivepoweranalysis-postprint.pdf although in practice we often talk about using pilot studies to get estimates fo...