Search found 49 matches
- Wed Jan 10, 2018 11:16 am
- Forum: Realcom user forum
- Topic: calculation of variance explained
- Replies: 1
- Views: 15835
Re: calculation of variance explained
Dear Lorraine If the multiple imputation has done its job properly, i.e. te assumptions are reasonable (MAR) then you dont need to have the same no of records for null modle and imputed model in order to study the relative amounts ofvariance explained in both cases since you should be getting unbias...
- Sun Oct 29, 2017 8:17 pm
- Forum: MLwiN user forum
- Topic: Mlwin supplement: autocorrelated errors in continuous time
- Replies: 2
- Views: 4866
Re: Mlwin supplement: autocorrelated errors in continuous time
That's right. If you have a binary response you need to move to a multivariate model. see
Barbosa and Goldstein (2000), Quality and quantity, 34, pp323-330
Barbosa and Goldstein (2000), Quality and quantity, 34, pp323-330
- Fri Feb 17, 2017 4:08 pm
- Forum: Realcom user forum
- Topic: How to impute a two-level model with repeated measures
- Replies: 5
- Views: 26193
Re: How to impute a two-level model with repeated measures
As I understand it, your model is a repeated measures model where you have some responses missing for some individuals at some occasions (months). If you just set this up as a 2-level model then there is typically no problem since the level 2 units (individuals) just have different numbers of level ...
- Tue Jan 10, 2017 3:17 pm
- Forum: runmlwin user forum
- Topic: Specifying Weights
- Replies: 2
- Views: 4622
Re: Specifying Weights
If you only have weights at 1 level then leave the weights at the other level as 'equal'. To use standardised weights just specify the weights column and check 'use standardised weights' in the menu box.
Harvey
Harvey
- Thu Apr 28, 2016 10:45 am
- Forum: MLwiN user forum
- Topic: Constraining the variance to zero.
- Replies: 2
- Views: 7294
Re: Constraining the variance to zero.
My view would be that all associated covariances should be constrained to zero also.
harvey
harvey
- Tue Feb 02, 2016 12:32 pm
- Forum: MLwiN user forum
- Topic: Multinomial logistic & VPC
- Replies: 2
- Views: 5100
Re: Multinomial logistic & VPC
What you suggest seems quite sensible to me and would apply whether you used IGlS or MCMC estimation. There is an analogous procedure for ordered data. You also might consider partitioning the covariances (correlations).
- Thu Jan 07, 2016 10:11 am
- Forum: Realcom user forum
- Topic: Realcom-imput / imputation model with missing values in explanatory variables
- Replies: 3
- Views: 16463
Re: Realcom-imput / imputation model with missing values in explanatory variables
You can impute several variables at a time - but it does not use chained equations. Explanatory variables in imputation model must have no missing values - if any have make them responses in imputation model.
- Mon Sep 28, 2015 5:41 pm
- Forum: MLwiN user forum
- Topic: cross-level interaction with Level-1 moderator
- Replies: 4
- Views: 21118
Re: cross-level interaction with Level-1 moderator
If I understand your model it seems to me that what you call the level 1 classification (am/pm) is actually a predictor variable and if you treat it as such then your analysis is straightforward, isn't it?
- Fri Sep 25, 2015 1:32 pm
- Forum: MLwiN user forum
- Topic: cross-level interaction with Level-1 moderator
- Replies: 4
- Views: 21118
Re: cross-level interaction with Level-1 moderator
Ignore previous post - should have read that it is inappropriate to predict a level 2 using a level 1 variable - this seems implicitly what is happening in your model.
- Fri Sep 25, 2015 1:26 pm
- Forum: MLwiN user forum
- Topic: cross-level interaction with Level-1 moderator
- Replies: 4
- Views: 21118
Re: cross-level interaction with Level-1 moderator
It typically doesn't make sense to predict a level 1 outcome using something defined at level 2. It can be specified but what happens is that such a model effectively induces dependencies among level 1 residuals. Also not easy to interpret.
Harvey Goldstein
Harvey Goldstein