[R-sig-ME] post hoc tests for glmmTMB

[Aoibheann Gaughran]

Great, thank you - I will keep plugging on. I will reconsider my use of the
Anova function in car as well!

On Fri, 9 Nov 2018 at 15:19, Ben Bolker <bbolker using gmail.com> wrote:

>
>   The point about Wald tests is correct, although their reliability
> depends very much on context (they should be pretty good for tests of
> fixed effects when the data set is reasonably large and predicted
> probabilities/counts are not too extreme, i.e. not too close to zero
> (counts) or 0/1 (probabilities)).
>
>   There are a lot of improvements in the development version with
> respect to post hoc tests etc. on glmmTMB fits, as documented here:
> <
> https://github.com/glmmTMB/glmmTMB/blob/master/glmmTMB/vignettes/model_evaluation.rmd
> >
>
>   If you can install the development version (see
> https://github.com/glmmTMB/glmmTMB/blob/master/README.md), that should
> help a lot.
>
>  If you can't, most of these improvements will probably get to CRAN in
> the next week or two; we're planning a new release soon.
>
>   In any case, I think that running the following code should make
> multcomp work with glmmTMB objects (not quite sure what that first
> function is doing ... ???)
>
> glht_glmmTMB <- function (model, ..., component="cond") {
>     glht(model, ...,
>          coef. = function(x) fixef(x)[[component]],
>          vcov. = function(x) vcov(x)[[component]],
>          df = NULL)
> }
> modelparm.glmmTMB <- function (model, coef. = function(x)
> fixef(x)[[component]],
>                                vcov. = function(x) vcov(x)[[component]],
>                                df = NULL, component="cond", ...) {
>     multcomp:::modelparm.default(model, coef. = coef., vcov. = vcov.,
>                         df = df, ...)
> }
>
> ## example
> g1 <- glht(cbpp_b1, linfct = mcp(period = "Tukey"))
>
>
>
> On 2018-11-09 9:42 a.m., Guillaume Adeux wrote:
> > Hi Aoibheann,
> >
> > I think that anova on glmmTMB objects only produce Wald tests, which
> don't
> > seem to be very reliable.
> > You might want to look at the monet package (or its little brother afex)
> > that can produce LRT tests or parametric bootstrap.
> >
> > Moreover, emmeans should work fine with glmmTMB but I remember having a
> > similar problem.
> >
> > Maybe this thread and the following discussion can help you out:
> >
> https://stackoverflow.com/questions/48609432/error-message-lsmeans-for-beta-mixed-regression-model-with-glmmtmb
> >
> > GA2
> >
> >
> >
> > Le ven. 9 nov. 2018 à 15:24, Aoibheann Gaughran <gaughra using tcd.ie> a
> écrit :
> >
> >> Update: lsmeans works if I use an older version of lsmeans (2.27-62) -
> can
> >> I rely on the results?
> >>
> >> Many thanks, Aoibheann
> >>
> >> On Fri, 9 Nov 2018 at 12:24, Aoibheann Gaughran <gaughra using tcd.ie> wrote:
> >>
> >>> Dear list,
> >>>
> >>> I am trying to perform post hoc tests on a glmmTMB model. I would
> >> normally
> >>> use car::Anova and mulgcomp::glht on my glmms (lmers). However, these
> >>> functions do not appear to be working for glmmTMB (when I run the model
> >> as
> >>> an lmer they work fine). I have also tried lsmeans and emmeans but they
> >> do
> >>> not appear to support glmmTMB either (although it appears they used
> to).
> >> I
> >>> have found various treads online suggesting that these functions should
> >>> work with TMB but they date back a few months.
> >>>
> >>> I am using the most up to date versions of R (3.5.1) and have updated
> all
> >>> of my packages e.g. glmmTMB 0.2.2.0, lsmeans 2.30-0
> >>>
> >>> The following are the error messages that I receive:
> >>>
> >>>> Anova(topmodTRFETE, type = 2)Error in I.p[c(subs.relatives,
> >> subs.term), , drop = FALSE] :
> >>>   subscript out of bound
> >>>
> >>>> summary(glht(topmodTRFETE, linfct = mcp(roadworks = "Tukey")), test =
> >> adjusted("holm"))Error in modelparm.default(model, ...) :
> >>>   dimensions of coefficients and covariance matrix don't match
> >>>>
> >>
> source(system.file("other_methods","lsmeans_methods.R",package="glmmTMB"))>
> >> lsmeans(topmodTRFETE, pairwise ~ roadworks, adjustSigma = TRUE, adjust =
> >> "holm")Error in ref_grid(object, ...) :
> >>>   Can't handle an object of class  “glmmTMB”
> >>>  Use help("models", package = "emmeans") for information on supported
> >> models.> rw.emm.s <- emmeans(topmodTRFETE, "roadworks")Error in
> >> ref_grid(object, ...) :
> >>>   Can't handle an object of class  “glmmTMB”
> >>>  Use help("models", package = "emmeans") for information on supported
> >> models.
> >>>
> >>>
> >>> Can any point me in the direction of a workaround for performing
> posthocs
> >>> on my glmmTMB model?
> >>>
> >>> Many thanks,
> >>>
> >>> --
> >>> Aoibheann Gaughran
> >>>
> >>> Behavioural and Evolutionary Ecology Research Group
> >>> Zoology Building
> >>> School of Natural Sciences
> >>> Trinity College Dublin
> >>> Dublin 2
> >>> Ireland
> >>> Phone: +353 (86) 3812615
> >>>
> >>
> >>
> >> --
> >> Aoibheann Gaughran
> >>
> >> Behavioural and Evolutionary Ecology Research Group
> >> Zoology Building
> >> School of Natural Sciences
> >> Trinity College Dublin
> >> Dublin 2
> >> Ireland
> >> Phone: +353 (86) 3812615
> >>
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> >>
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> >>
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-- 
Aoibheann Gaughran

Behavioural and Evolutionary Ecology Research Group
Zoology Building
School of Natural Sciences
Trinity College Dublin
Dublin 2
Ireland
Phone: +353 (86) 3812615

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