You should read the manual that is on the website. It does not used chained equations and you can spcify missing data anywhere and imputed values are available.
Harvey Goldstein
Search found 49 matches
- Thu May 28, 2015 3:17 pm
- Forum: Realcom user forum
- Topic: Realcom-imput / imputation model with missing values in explanatory variables
- Replies: 3
- Views: 17674
- Sat Feb 14, 2015 1:15 pm
- Forum: Realcom user forum
- Topic: Imputation and perfect prediction
- Replies: 2
- Views: 5493
Re: Imputation and perfect prediction
We haven't really explored this. There are some bounds that are placed around draws that may deal with this, but you would do best to avoid perfect predictions if you can. Interested to know if it works for you however.
Harvey Goldstein
Harvey Goldstein
- Sat Feb 14, 2015 2:03 am
- Forum: Realcom user forum
- Topic: Include level1 variables to impute level 2 missing variable
- Replies: 1
- Views: 5059
Re: Include level1 variables to impute level 2 missing variable
When you specify a 2 level imputation model any level 1 variables that are declared responses at level 1 implicitly contribute through their level 2 random effects. However you cannot have a level 1 predictor for a level 2 response in any multilevel model so do not include level 1 variables as covar...
- Fri Dec 12, 2014 6:18 pm
- Forum: Realcom user forum
- Topic: Imputation and perfect prediction
- Replies: 2
- Views: 5493
Re: Imputation and perfect prediction
There is no feature in realcom to do this I'm afraid.
Harvey Goldstein
Harvey Goldstein
- Wed Sep 03, 2014 10:32 am
- Forum: MLwiN user forum
- Topic: Missing data: FIML and (multilevel) multiple imputation
- Replies: 1
- Views: 4650
Re: Missing data: FIML and (multilevel) multiple imputation
The IGLS estimates are indeed maximum likelihood ones. Re missing data the mlwin default is listwise deletion of all level 1 records where any model variable has a missing value. If you wish to do an efficient multiple imputation on 2-level data you have two possibilities now. Either REALCOM which h...
- Mon Jun 16, 2014 1:34 pm
- Forum: Realcom user forum
- Topic: model with level 2 missings only
- Replies: 3
- Views: 7241
Re: model with level 2 missings only
Should be original 2 level dataset
Harvey
Harvey
- Sat Jun 14, 2014 8:44 pm
- Forum: Realcom user forum
- Topic: model with level 2 missings only
- Replies: 3
- Views: 7241
Re: model with level 2 missings only
Yes - that should be fine. Let me know if there are any problems.
Harvey Goldstein
Harvey Goldstein
- Thu Apr 10, 2014 2:17 pm
- Forum: Realcom user forum
- Topic: Imputation very slow
- Replies: 7
- Views: 11231
Re: Imputation very slow
Yes - imputation can be slow. We are switching now to STATJR (see CMM web site) and a 2-level imputation module has just been put up there - use of this is free.
You should ideally put all variables in as responses.
Harvey Goldstein
You should ideally put all variables in as responses.
Harvey Goldstein
- Mon Mar 03, 2014 2:52 pm
- Forum: Realcom user forum
- Topic: 2 level vs. single level imputation model
- Replies: 6
- Views: 9779
Re: 2 level vs. single level imputation model
All variables in the MOI, whether responses or predictors do need to be in the imputation model.
- Mon Mar 03, 2014 2:00 pm
- Forum: Realcom user forum
- Topic: 2 level vs. single level imputation model
- Replies: 6
- Views: 9779
Re: 2 level vs. single level imputation model
Strictly speaking you should set up a 2-level imputation model where any level 1 vbles in the MOI are responses (at level 1 in the imputation model).
Harvey Goldstein
Harvey Goldstein