[R-sig-ME] Error fitting reduced model in bglmer for LRT

[Josie Galbraith]

Thanks Vince.
So should I just use the Wald-Z output instead then? Or another method of
inference? Any ideas which is best in this situation?

The code for the temp fix didn't work for me (see below).  But that may not
be important if I use another method of inference...

Cheers,
Josie

> assignInNamespace("toString.bmerTDist", function(x, digits =
getOption("digits"), ...) {
+   scaleString <- ""
+   scale <- crossprod(solve(x at R.scale.inv))
Error: unexpected symbol in:
"  scaleString <- ""
  scale <- crossprod(solve(x at"
>
>   if (nrow(scale) > 2) {
+     scaleString <- paste("scale = c(", toString(round(scale[1:4],
digits)), ", ...)", sep = "")
+   } else if (nrow(scale) == 2) {
+     scaleString <- paste("scale = c(", toString(round(scale[1:4],
digits)), ")", sep = "")
+   } else {
+     scaleString <- paste("scale = ", toString(round(scale[1], digits)),
sep = "")
+   }
Error in if (nrow(scale) > 2) { : argument is of length zero
>
>   paste("t(df = ", x at df, ", ", scaleString,
Error: unexpected symbol in "  paste("t(df = ", x at"
>         ", common.scale = ", x at commonScale,
Error: unexpected ',' in "        ", common.scale = ","
>         ")", sep="")
Error: unexpected ',' in "        ")","
> }, "blme")
Error: unexpected '}' in "}"
>





Date: Tue, 10 Mar 2015 13:23:22 -0400
> From: Vincent Dorie <vjd4 at nyu.edu>
> To: r-sig-mixed-models at r-project.org
> Subject: Re: [R-sig-ME] Error fitting reduced model in bglmer for LRT
> Message-ID: <9FBE19D0-EA83-4F5B-8333-0C52C18390D9 at nyu.edu>
> Content-Type: text/plain; charset=utf-8
>
> I don't know what exactly anova() does for glmms, but I wouldn't recommend
> a likelihood ratio test to compare posterior modes unless you can be
> certain the data swamp the prior.
>
> The error you experienced is a copy/paste error on my part. You can run
> the code below to fix it temporarily, until I can get a new release on CRAN.
>
> assignInNamespace("toString.bmerTDist", function(x, digits =
> getOption("digits"), ...) {
>   scaleString <- ""
>   scale <- crossprod(solve(x at R.scale.inv))
>
>   if (nrow(scale) > 2) {
>     scaleString <- paste("scale = c(", toString(round(scale[1:4],
> digits)), ", ...)", sep = "")
>   } else if (nrow(scale) == 2) {
>     scaleString <- paste("scale = c(", toString(round(scale[1:4],
> digits)), ")", sep = "")
>   } else {
>     scaleString <- paste("scale = ", toString(round(scale[1], digits)),
> sep = "")
>   }
>
>   paste("t(df = ", x at df, ", ", scaleString,
>         ", common.scale = ", x at commonScale,
>         ")", sep="")
> }, "blme")
>
> Vince
>
> > On Mar 9, 2015, at 11:47 PM, Josie Galbraith <josie.galbraith at gmail.com>
> wrote:
> >
> > Hi all,
> >
> > In following on from this post
> > <https://stat.ethz.ch/pipermail/r-sig-mixed-models/2015q1/023191.html>,
> > regarding using blme and fixed effect priors to address issues of
> complete
> > separation in my data, I've come up against a problem trying to fit
> reduced
> > models for testing the model terms using likelihood ratio tests (LRT).
> >
> > Firstly, can I use LRTs (anova()) for testing the fixed effects of bglmer
> > models, as I would for glmer models?
> >
> > If yes, then I need help understanding why I'm getting the following
> error
> > fitting a reduced bglmer model:
> > "Error in if (nrow(cov) == 2) { : argument is of length zero"
> >
> > This is my full model:
> > SE.les.mod = bglmer (LESION ~ FOOD*SEASON +(1|SITE), data = SEYE.df,
> family
> > = binomial, fixef.prior = t(1,2.5), cov.prior = NULL)
> >
> > I can fit a model without the interaction term ok:
> > SE.les.add = bglmer (LESION ~ FOOD+SEASON +(1|SITE), data = SEYE.df,
> family
> > = binomial, fixef.prior = t(1,2.5), cov.prior = NULL)
> >
> > But I get the error message with both of the single fixed effects models:
> > SE.les.FOOD = bglmer (LESION ~ SEASON +(1|SITE), data = SEYE.df, family =
> > binomial, fixef.prior = t(1,2.5), cov.prior = NULL)
> > SE.les.SEAS = bglmer (LESION ~ FOOD +(1|SITE), data = SEYE.df, family =
> > binomial, fixef.prior = t(1,2.5), cov.prior = NULL)
> >
> > Thanks very much,
> > Josie
> >
> >
> >
> > --
> > *Josie Galbraith* MSc (hons)
> >
> > PhD candidate
> > *University of Auckland *
> > Joint Graduate School in Biodiversity and Biosecurity ? School of
> > Biological Sciences ? Tamaki Campus ? Private Bag 92019 ? Auckland 1142*
> ?
> > P:* 09-373 7599 ext. 83132* ? E:* josie.galbraith at gmail.com* ? W: * UoA
> Web
> > Profile <https://unidirectory.auckland.ac.nz/profile/jgal026> and
> > *www.birdfeedingnz.weebly.com/* <http://birdfeedingnz.weebly.com/>
> >
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> >
> > _______________________________________________
> > R-sig-mixed-models at r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>
>
>
> --
*Josie Galbraith* MSc (hons)

PhD candidate
*University of Auckland *
Joint Graduate School in Biodiversity and Biosecurity ● School of
Biological Sciences ● Tamaki Campus ● Private Bag 92019 ● Auckland 1142* ●
P:* 09-373 7599 ext. 83132* ● E:* josie.galbraith at gmail.com* ● W: * UoA Web
Profile <https://unidirectory.auckland.ac.nz/profile/jgal026> and
*www.birdfeedingnz.weebly.com/* <http://birdfeedingnz.weebly.com/>

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