From: Søren Højsgaard <Soren.Hojsgaard_at_agrsci.dk>

Date: Sun 29 Jan 2006 - 23:17:01 EST

Date: Sun 29 Jan 2006 - 23:17:01 EST

In connection with calculating Monte Carlo p-values based on sampled data sets: The calculations involve something like

update(lmer.model, data=newdata)

where newdata is a simulated dataset comming from simulate(lmer.model). I guess the update could be faster if one could supply the update function with the parameter estimates from the original fit of the lmer.model as starting values. Is this possible to achieve??
Best

Søren

Fra: pd@pubhealth.ku.dk på vegne af Peter Dalgaard
Sendt: lø 28-01-2006 01:12

Til: Douglas Bates

Cc: Søren Højsgaard; R-help@stat.math.ethz.ch
Emne: Re: [R] how calculation degrees freedom

Douglas Bates <dmbates@gmail.com> writes:

> > Of course, Monte Carlo p-values have their problems, but the world

*> > is not perfect....
**>
**> Another approach is to use mcmcsamp to derive a sample from the
**> posterior distribution of the parameters using Markov Chain Monte
**> Carlo sampling. If you are interested in intervals rather than
**> p-values the HPDinterval function from the coda package can create
**> those.
**>
*

We (Søren and I) actually had a look at that, and it seems not to solve the problem. Rather, mcmcsamp tends to reproduce the Wald style inference (infinite DF) if you use a suitably vague prior.

It's a bit hard to understand clearly, but I think the crux is that any Bayes inference only depends on data through the likelihood function. The distribution of the likelihood never enters (the hardcore Bayesian of course won't care). However, the nature of DF corrections is that the LRT does not have its asymptotic distribution, and mcmc has no way of picking that up.

-- O__ ---- Peter Dalgaard Øster Farimagsgade 5, Entr.B c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 ~~~~~~~~~~ - (p.dalgaard@biostat.ku.dk) FAX: (+45) 35327907 ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.htmlReceived on Sun Jan 29 23:28:08 2006

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