Search found 156 matches
- Fri Aug 10, 2018 4:40 pm
- Forum: MLwiN user forum
- Topic: Power/Effective Sample Size
- Replies: 5
- Views: 14023
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...
- Mon Aug 06, 2018 7:43 am
- Forum: R2MLwiN user forum
- Topic: Different ESS in MLwiN and R2MLwiN
- Replies: 11
- Views: 22438
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...
- 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: 3629
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 ...
- Tue May 29, 2018 1:50 pm
- Forum: runmlwin user forum
- Topic: Can runmlwin handle CAR models at two levels?
- Replies: 3
- Views: 5551
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!)
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!)
- Mon May 21, 2018 10:28 am
- Forum: runmlwin user forum
- Topic: Can runmlwin handle CAR models at two levels?
- Replies: 3
- Views: 5551
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...
- Sat May 12, 2018 7:26 am
- Forum: MLwiN user forum
- Topic: MLPowSim macro not working in MLWin
- Replies: 3
- Views: 5100
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.
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.
- Tue Apr 24, 2018 10:48 am
- Forum: MLwiN user forum
- Topic: Heteroscedasticity and robust standard errors
- Replies: 1
- Views: 3774
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.
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.
- Mon Apr 16, 2018 8:56 am
- Forum: MLwiN user forum
- Topic: Testing Nested Models
- Replies: 2
- Views: 4870
Re: Testing Nested Models
Hi Nick, That's quite tricky. If you are using classical estimation then you can do an approximate Wald test though this isn't so great as assumes normality for the variance parameter. Alternatively you can use the DIC diagnostic with MCMC estimation although again this is not universally liked but ...
- Thu Apr 12, 2018 2:33 pm
- Forum: MLwiN user forum
- Topic: Confidence intervals for variance function
- Replies: 3
- Views: 5206
Re: Confidence intervals for variance function
Hi Jerome, If you look at my MCMC book then in section 4.9 I describe how one works out estimates and confidence intervals for functions of parameters - in this case a VPC and so you could do something similar. Perhaps an even easier solution is to to reparameterise your model so that you don't have...
- Thu Apr 12, 2018 1:44 pm
- Forum: MLwiN user forum
- Topic: Confidence intervals for variance function
- Replies: 3
- Views: 5206
Re: Confidence intervals for variance function
Hi Jerome, It's not usually the case that variances follow normal distributions but you would get an approximate interval using the SE. If you used MCMC estimation then you could get a chain of variance functions and thus an empirical credible interval for the 2 variances. Don't know if that is help...