Search found 430 matches

by GeorgeLeckie
Wed Aug 10, 2016 2:18 pm
Forum: MLwiN user forum
Topic: Data set up Longitudinal Multiple Membership Model
Replies: 11
Views: 11259

Re: Data set up Longitudinal Multiple Membership Model

Hi Gerine,

If you haven't already done so, I recommend that you read the Multiple Membership module of our LEMMA online course for a good overview of what these models can and can't do.

Hope that helps

George
by GeorgeLeckie
Tue Aug 09, 2016 12:09 pm
Forum: MLwiN user forum
Topic: Data set up Longitudinal Multiple Membership Model
Replies: 11
Views: 11259

Re: Data set up Longitudinal Multiple Membership Model

Hi Gerine, MlwiN like all standard software will listwise delete the data (drop rows where there are one or more missing values in the response or covariates) prior to fitting any specified model. So it depends on what you intend to do with your data. If you want to regress grade 8 score on grade 5,...
by GeorgeLeckie
Mon Aug 08, 2016 3:53 pm
Forum: MLwiN user forum
Topic: Data set up Longitudinal Multiple Membership Model
Replies: 11
Views: 11259

Re: Data set up Longitudinal Multiple Membership Model

Hi Gerine, Its all about the level-1 observations. Each observation belongs to one child, one class and one school. The data are therefore cross-classified rather than multiple membership. So what you want to do is fit cross-classified models rather than multiple membership models. I hope that helps...
by GeorgeLeckie
Wed Aug 03, 2016 4:02 pm
Forum: runmlwin user forum
Topic: query on calculation of probability predictions
Replies: 3
Views: 3405

Re: query on calculation of probability predictions

Hi Bernie, Thanks for providing the full runmlwin syntax. It looks correct for specifying a cross-classified model. Each response measurement belongs to only one interviewer so do not refer to the data structure or the above model as multiple membership as this implies that each response measurement...
by GeorgeLeckie
Tue Aug 02, 2016 4:28 pm
Forum: runmlwin user forum
Topic: Predicted Probability for ML Ordinal Model
Replies: 3
Views: 3068

Re: Predicted Probability for ML Ordinal Model

Hi Vivian,

As far as I can see what you have done looks correct. I am guessing that the other 12 rows correspond to scenarios where two or more dummies are switched on simultaneously which of course do not make sense in your example. So yes ignore these 12 other rows.

Best wishes

George
by GeorgeLeckie
Tue Aug 02, 2016 12:21 pm
Forum: runmlwin user forum
Topic: query on calculation of probability predictions
Replies: 3
Views: 3405

Re: query on calculation of probability predictions

Hi Bernie, The data sound cross-classified rather than multiple membership. Each response score belongs to one respondent and one interviewer rather than multiple individuals or multiple interviewers. In terms of your runmlwin syntax, I wasn't clear to what the xwaveid identifer referred to. You als...
by GeorgeLeckie
Tue Aug 02, 2016 11:43 am
Forum: MLwiN user forum
Topic: Data set up Longitudinal Multiple Membership Model
Replies: 11
Views: 11259

Re: Data set up Longitudinal Multiple Membership Model

Hi Gerine, There is a lot of information here. However, as far as I can see your scores are the level-1 units in cross-classified data structure rather than a multiple membership structure. You have a separate score for each child in each wave. So each score is associated with one child, one class a...
by GeorgeLeckie
Tue Aug 02, 2016 11:30 am
Forum: runmlwin user forum
Topic: Predicted Probability for ML Ordinal Model
Replies: 3
Views: 3068

Re: Predicted Probability for ML Ordinal Model

Hi Vivian, Yes. What you have done should work. Please can you send through more details about the MLwiN crash. Alternatively, the more "runmlwin" approach would be to calculate these predicted probabilities in Stata. See http://www.bristol.ac.uk/cmm/media/runmlwin/11_Fitting_an_Ordered_Category_Res...
by GeorgeLeckie
Fri May 20, 2016 4:02 pm
Forum: runmlwin user forum
Topic: Question VPC calculation
Replies: 1
Views: 1928

Re: Question VPC calculation

Dear Mahadev11,

Suggest you calculate VPCs based on the latent response formulation of the logistic regression model. See Module 7 of the LEMMA online course (Section 7.2) or any decent multilevel textbook for details.

Best wishes

George
by GeorgeLeckie
Tue May 03, 2016 3:50 pm
Forum: runmlwin user forum
Topic: Random effects prediction and interpretation in multilevel logit models
Replies: 2
Views: 2585

Re: Random effects prediction and interpretation in multilevel logit models

Dear rahulvbb,

The predicted state random effects measure how much higher the predicted log-odds are in each state relative to the average state.

Researchers often plot these in a caterpillar plot to aide graphical interpretation. You can do this using the -serrbar- command.

Best wishes

George