Search found 425 matches

by GeorgeLeckie
Tue Jul 23, 2019 9:33 am
Forum: runmlwin user forum
Topic: jackknife replicate weight in runmlwin
Replies: 2
Views: 58

Re: jackknife replicate weight in runmlwin

Hi Sun Lee, Yes you can specify weights in runmlwin. You need to specify weights at each level in the model. See the help file and search for "weight" to find the weights options. Unfortunately we do not have an example to show you. There is an example in the Stata ME manual for their -mixed- comman...
by GeorgeLeckie
Mon Jul 08, 2019 12:04 pm
Forum: runmlwin user forum
Topic: Mixed-effects, mixed distribution model
Replies: 1
Views: 1650

Re: Mixed-effects, mixed distribution model

Dear Gujarish, No you cannot fit this specific model in MLwiN. For these data, what you could do in MLwiN is fit the analyses in two parts. First, fit a multilevel model for whether peopled walked at all (0 steps vs 1+ steps) Then for the subset who had 1+ steps you could fit a multilevel model for ...
by GeorgeLeckie
Mon Jun 10, 2019 9:09 am
Forum: runmlwin user forum
Topic: autocorrelation problem in within-between random effect model
Replies: 10
Views: 959

Re: autocorrelation problem in within-between random effect model

Dear umitotakao,

You can specify cluster robust standard errors in runmlwin

See the fpsandwich option

Note. If you wish to exclude the random effect from the model then you will need to constrain this parameter to zero, otherwise MLwiN won't know what the clusters are.

Best wishes

George
by GeorgeLeckie
Mon Apr 01, 2019 1:41 pm
Forum: MLwiN user forum
Topic: Level-2 variance be zero
Replies: 1
Views: 372

Re: Level-2 variance be zero

Dear Helanidilk, This all sounds fine. Yes, when you set the true cluster variance to be small, in some simulated datasets the estimated cluster variance will be zero. Yes, this is part of the sampling variability of the cluster variance. Note, you should not drop the simulations which give estimate...
by GeorgeLeckie
Tue Dec 18, 2018 4:57 pm
Forum: runmlwin user forum
Topic: Illustrate lower-level interaction by use of a graph similar to margins command
Replies: 2
Views: 723

Re: Illustrate lower-level interaction by use of a graph similar to margins command

Dear KazimovHH, There is a lot going on here, but at least from a quick scan it looks like you are doing something sensible. You fit your three level model You then set all variables to zero except for the the two variables of interest (one of which is binary, the other continuous) You then predict ...
by GeorgeLeckie
Tue Dec 18, 2018 4:50 pm
Forum: runmlwin user forum
Topic: Cross-level interaction specification in multilevel logit
Replies: 2
Views: 700

Re: Cross-level interaction specification in multilevel logit

Hi, Yes, your first code and interpretation is correct. In your second code you should include the fixed effect of z3. Including z3 in the random part of the model allows the between-country variance to be a function of country characteristics z3. A heteroskedastic relationship. There is no random s...
by GeorgeLeckie
Thu Nov 29, 2018 11:41 am
Forum: runmlwin user forum
Topic: predict probability and CI
Replies: 3
Views: 797

Re: predict probability and CI

Hi Rodrigo,

That is correct runmlwin is not comaptabile with margins.

However, you should be able to do what you want simply by using the nlcom command to calculate the expression you have written out.

Best wishes

George
by GeorgeLeckie
Thu Nov 22, 2018 11:01 am
Forum: runmlwin user forum
Topic: p value in mcmc model
Replies: 2
Views: 652

Re: p value in mcmc model

Dear Rodrigo, The default presented p-value is a Bayesian one-sided p-value (the proportion of the MCMC chain which is the opposite sign to the point estimate). You report a p-value of 0.049 so a conventional two-sided p-value would be more like 0.100 You can actually request the 'properly calculate...
by GeorgeLeckie
Mon Oct 22, 2018 3:44 pm
Forum: runmlwin user forum
Topic: negative binomial example for runmlwin
Replies: 2
Views: 1641

Re: negative binomial example for runmlwin

Dear Ralph, We don't currently have any worked examples, however, here is how you fit the mean dispersion or NB2 version of the negative binomial model in MLwiN for the simple case of one-level data where we have one predictor . runmlwin y cons x, /// level1(id:) /// discrete(distribution(nbinomial)...
by GeorgeLeckie
Tue Oct 09, 2018 4:02 pm
Forum: runmlwin user forum
Topic: Interpretation of the between-country variance as a function of 'x', random slope
Replies: 2
Views: 1462

Re: Interpretation of the between-country variance as a function of 'x', random slope

Negative covariance means that the variance function will be decreasing when x = 0. It will however, increase again eventually at higher values of x and this is what you see.

Similarly, you will see fanning in at x = 0, but will see fanning out again at higher values of x.