Search found 57 matches

by richardparker
Mon Dec 12, 2016 4:07 pm
Forum: MLwiN user forum
Topic: longitudinal data (multilevel- 3 levels) with missing data at level 1
Replies: 6
Views: 7707

Re: longitudinal data (multilevel- 3 levels) with missing data at level 1

Hi - sorry I didn't have the opportunity to reply to your earlier post - if you just have missing data in your (univariate) response in your model of interest, then imputing values via multiple imputation will not contribute any further information to your analysis - e.g. the introductory section of...
by richardparker
Fri Dec 02, 2016 2:45 pm
Forum: MLwiN user forum
Topic: longitudinal data (multilevel- 3 levels) with missing data at level 1
Replies: 6
Views: 7707

Re: longitudinal data (multilevel- 3 levels) with missing data at level 1

Hi - can I just check: did you install the C++ compiler MinGW? Instructions can be found here: http://www.bristol.ac.uk/cmm/software/s ... stallation

Best wishes,

Richard
by richardparker
Wed Nov 30, 2016 10:05 am
Forum: MLwiN user forum
Topic: longitudinal data (multilevel- 3 levels) with missing data at level 1
Replies: 6
Views: 7707

Re: longitudinal data (multilevel- 3 levels) with missing data at level 1

Hi Mansoor - you might be interested in new functionality which has recently been released to support the analyses of incomplete datasets in Stat-JR (distributed with MLwiN); see http://www.bristol.ac.uk/cmm/news/2016/85.html . This new functionality includes a template (NLevelImpute) which performs...
by richardparker
Mon Oct 24, 2016 10:00 am
Forum: R2MLwiN user forum
Topic: Confidence Intervals vs. Significant p-values
Replies: 1
Views: 1656

Re: Confidence Intervals vs. Significant p-values

Note that one-sided Bayesian p-values are another option which can be helpful; these can be toggled on/off in R2MLwiN via z.ratio. There is an example in Section 6 of the R2MLwiN article ( http://dx.doi.org/10.18637/jss.v072.i10 ) recently published in the Journal of Statistical Software; as the art...
by richardparker
Wed Oct 14, 2015 2:22 pm
Forum: R2MLwiN user forum
Topic: R2MlwiN error - ... iteration aborted
Replies: 2
Views: 1871

Re: R2MlwiN error - ... iteration aborted

Hi - the error you are getting is from MLwiN, and it suggests it is having difficulties estimating the model you have specified (given the data). Since you have a large number of fixed effects (as each of the factors will consist of a number of levels, and so a relatively large number of dummy varia...
by richardparker
Thu Sep 24, 2015 12:49 pm
Forum: Stat-JR user forum
Topic: How to use command line interface?
Replies: 3
Views: 2444

Re: How to use command line interface?

Hi - thanks for your interest in the software. The forum message Chris linked to illustrates how to call Stat-JR from R and bring the results back. It's not actually necessary to write a Stat-JR template in order to do that (one can use the templates provided in the Stat-JR package), although it wou...
by richardparker
Tue Aug 18, 2015 4:01 pm
Forum: MLwiN user forum
Topic: Removing the (random) intercept
Replies: 3
Views: 2177

Re: Removing the (random) intercept

Hi - yes, that was my understanding: I don't think it makes sense to try to estimate an overall intercept variance (and its covariances) at level 2 when the coefficients of all the dummy variables of a categorical predictor (i.e. all three dummies from a categorical variable consisting of three cate...
by richardparker
Mon Aug 17, 2015 4:23 pm
Forum: MLwiN user forum
Topic: Removing the (random) intercept
Replies: 3
Views: 2177

Re: Removing the (random) intercept

Hi - I've tried to roughly replicate your scenario with one of the sample datasets (tutorial): library(R2MLwiN) data("tutorial") my_tutorial <- tutorial # create new factor variable standlrt_cat from standlrt, consisting of low/mid/high my_tutorial$standlrt_cat[my_tutorial$standlrt < -1] <- "low" my...
by richardparker
Tue May 26, 2015 9:47 am
Forum: Stat-JR user forum
Topic: installation issue?
Replies: 6
Views: 3534

Re: installation issue?

Hi - are you able to provide any more information about the issue you have encountered? The resolution to the problem described earlier in this thread was to change the name of one of the variables in the dataset - it had a character (@) which was unsupported by Stat-JR.

Best wishes,

Richard
by richardparker
Fri Jan 16, 2015 3:44 pm
Forum: Stat-JR user forum
Topic: Random intercept vs. random slopes in 2LevelImpute
Replies: 34
Views: 17686

Re: Random intercept vs. random slopes in 2LevelImpute

Hi - I'm sorry to hear you've lost the results pane; yes, safer to switch to compatibility mode on an occasion when you're starting Stat-JR afresh - apologies I didn't make that clearer. You should be able to recover all your outputs from your downloaded results, however: e.g. WordPad is a good choi...