Will do.

Jake

> Date: Mon, 19 May 2014 14:28:47 -0400
> From: bbolker@gmail.com
> To: r-sig-mixed-models@r-project.org
> Subject: Re: [R-sig-ME] "parm" parameter in lme4::confint.merMod
> 
> On 14-05-19 02:24 PM, Jake Westfall wrote:
> > Thanks Ben, it looks like a slight tweaking of your command should
> > work:
> > 
> > c(names(getME(sig0,c("theta"))), names(fixef(sig0)))
> > 
> > Although (not sure if this is the right thread for this but here
> > goes) I'm having trouble verifying that the order matches because,
> > from what I can tell, confint.merMod() does not appear to work for
> > profile confidence intervals for models that include covariance
> > parameters between random terms. I always get an error about
> > "Starting values violate bounds" and additionally some warnings about
> > non-monotonic profiles. If I fix the covariance at 0 then
> > confint.merMod() works fine for profile confidence intervals. I could
> > send more info if you'd like, but it sounds like maybe you are aware
> > of this already. Jake
> 
> 
>   I'm vaguely aware of it, but it would be great if you were able to add
> an issue (with simple reproducible example) at
> https://github.com/lme4/lme4/issues ...
> 
>   cheers
>     Ben
> 
> 
> >> Date: Sun, 18 May 2014 10:21:00 -0400 From: bbolker@gmail.com To:
> >> henrik.singmann@psychologie.uni-freiburg.de;
> >> r-sig-mixed-models@r-project.org Subject: Re: [R-sig-ME] "parm"
> >> parameter in lme4::confint.merMod
> >> 
> >> On 14-05-18 07:34 AM, Henrik Singmann wrote:
> >>> Hi Jake,
> >>> 
> >>> I think fixef() or names(fixef()) gives you what you want:
> >> 
> >> I don't think it gets you everything.  Your solution works in the
> >> method="Wald" case because method="Wald" only returns the fixed
> >> effects, so one only has to keep track of those positions.
> >> method="profile" and "boot" include both variance-covariance and
> >> fixed effect parameters, in that order. Some possibilities are
> >> 
> >> names(unlist(getME(m1,c("theta","fixef")))) ## this gives names of
> >> 'theta' parameters (i.e. Cholesky factors) ## rather than standard
> >> deviations/correlations, but I believe ## the order is the same
> >> 
> >> ## theta parameters only (hidden function) lme4:::tnames(m1)
> >> 
> >> require(lme4) data(md_16.4, package = "afex") m1 <-  lmer(induct ~
> >> cond*cog + (cog|room:cond), md_16.4)
> >> 
> >> ## I actually had some problems with profiling this example -- ##
> >> not quite sure why.  Will have to look into it. pp <- profile(m1)
> >> 
> >> 
> >> confint(m1,parm=3)
> >>> fixef(m1) ## (Intercept)       cond1         cog   cond1:cog ##
> >>> -6.14153043 10.32001485  0.66722061 -0.02520666
> >>> 
> >>> confint(m1, parm = c(3,2), method="Wald") ##             2.5 %
> >>> 97.5 % ## cog     0.2498764  1.084565 ## cond1 -18.4845630
> >>> 39.124593
> >>> 
> >>> I hope I didn't misunderstand your question, Henrik
> >>> 
> >>> 
> >>> Am 18.05.2014 08:03, schrieb Jake Westfall:
> >>>> Hi all,
> >>>> 
> >>>> According to the documentation, in confint.merMod() you can use
> >>>> the "parm" parameter to get confidence intervals for only a
> >>>> specified subset of parameters by indicating the integer
> >>>> positions of the desired parameters. But how is one supposed to
> >>>> know which integer positions correspond with which parameters?
> >>>> I poked around a little but found nothing in the methods or
> >>>> slots of the merMod object that indicates this, and nothing in
> >>>> the documentation detailing this. Have I missed something? I
> >>>> guess you can call the function leaving that argument at its
> >>>> default, and the order of the parameters in that output will
> >>>> correspond with the integer positions, but this approach would
> >>>> seem to defeat the point of being able to specify particular 
> >>>> subsets of parameters...
> >>>> 
> >>>> Jake [[alternative HTML version deleted]]
> >>>> 
> >>> 
> >> 
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