Search found 139 matches

by billb
Tue Oct 16, 2018 3:47 pm
Forum: MLwiN user forum
Topic: Finite population correction
Replies: 3
Views: 3371

Re: Finite population correction

Hi John,
There isn't a whole lot of literature on FPCs for multilevel models and MLwiN assumes an infinite population in all it's calculations. A search will find a few recent papers if you are interested.
Best wishes,
Bill.
by billb
Mon Oct 15, 2018 1:22 pm
Forum: runmlwin user forum
Topic: Cross-classified logit model: Getting the ICCs
Replies: 8
Views: 6404

Re: Cross-classified logit model: Getting the ICCs

Hi Johannes, I am not sure here whether you mean ICC or VPC but I can offer the paper I wrote on variance partitioning in multilevel logistic models (Browne et al., 2005 JRSS A https://rss.onlinelibrary.wiley.com/doi/full/10.1111/j.1467-985X.2004.00365.x ). This covers overdispersed models which are...
by billb
Fri Oct 05, 2018 10:23 am
Forum: runmlwin user forum
Topic: Specifying orthogonal in Hierarchical Centring decreases ESS
Replies: 2
Views: 3509

Re: Specifying orthogonal in Hierarchical Centring decreases ESS

Hi KazimovHH, Thanks for the email. Hard to know what the right answer here as you have 2 techniques (Orthogonal parameterisation and Hierarchical centering) which do different things and can both improve mixing for particular model features so the answer will depend on your particular dataset. Orth...
by billb
Fri Aug 10, 2018 4:40 pm
Forum: MLwiN user forum
Topic: Power/Effective Sample Size
Replies: 5
Views: 4606

Re: Power/Effective Sample Size

Hi Divyamore, Just to reiterate my reply to Jillian. MCMC has a concept called effective sample size which has nothing to do with power but is the number of effective independent iterations of an MCMC chain run. This is what MLwiN is reporting (and I should know as one of the programmers!) and altho...
by billb
Mon Aug 06, 2018 7:43 am
Forum: R2MLwiN user forum
Topic: Different ESS in MLwiN and R2MLwiN
Replies: 11
Views: 12123

Re: Different ESS in MLwiN and R2MLwiN

Morning Andy and Chris, When I wrote the ESS calculation in MLwiN 20 odd years ago as you'll see I decided to limit the calculation to the first 1000 elements of the autocorrelation function probably partly because of time/space considerations (computers were slower at the time) and partly because i...
by billb
Mon Jul 30, 2018 8:50 am
Forum: runmlwin user forum
Topic: cross-classified/cross-nested model: How to get all relevant random components
Replies: 1
Views: 1938

Re: cross-classified/cross-nested model: How to get all relevant random components

Hi Johannes, Basically in MLwiN (and therefore RunMLwiN) the classifications fitted are the ones you specify - in this case the 4 given each with a set of random effects. If you want to include 'interaction classifications' you need to create the appropriate variables and declare them as additional ...
by billb
Tue May 29, 2018 1:50 pm
Forum: runmlwin user forum
Topic: Can runmlwin handle CAR models at two levels?
Replies: 3
Views: 3366

Re: Can runmlwin handle CAR models at two levels?

Hi Yusuf,
I guess you could and the dependence structure would presumably be easy with each year a neighbour of it's next and last but this is answering something completely different as this would be overall year effects and not different year effects per neighbourhood.
Best wishes,
Bill (no y!)
by billb
Mon May 21, 2018 10:28 am
Forum: runmlwin user forum
Topic: Can runmlwin handle CAR models at two levels?
Replies: 3
Views: 3366

Re: Can runmlwin handle CAR models at two levels?

Hi Yransome, The CAR modelling in MLwiN (and hence runMLwiN) is limited to only having a constant random at the CAR distributed residuals level i.e. we can't include a spatially varying random slope in a CAR model. We did extend the CAR modelling so that you could have different levels of CAR residu...
by billb
Sat May 12, 2018 7:26 am
Forum: MLwiN user forum
Topic: MLPowSim macro not working in MLWin
Replies: 3
Views: 3088

Re: MLPowSim macro not working in MLWin

Hi Adam80090,
I'll pass that on to my colleague Chris Charlton as I am sure we can probably fix this in the software - I wrote the MCMC functionality but not the core code so this one will be in Chris's domain.
Thanks for pointing it out.
Bill.
by billb
Tue Apr 24, 2018 10:48 am
Forum: MLwiN user forum
Topic: Heteroscedasticity and robust standard errors
Replies: 1
Views: 2352

Re: Heteroscedasticity and robust standard errors

Hi,
I am not sure precisely what model and what robust ses you refer to here. Generally in MCMC one would look at credible intervals if one wanted to get confidence intervals that are not restricted to normality so perhaps just use them.
Bill.