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

Ben Bolker bbolker @ending from gm@il@com
Fri Nov 9 16:27:57 CET 2018 

  The devel version of glmmTMB contains Anova methods for glmmTMB :

https://github.com/glmmTMB/glmmTMB/blob/master/glmmTMB/R/Anova.R

 cheers
  Ben

On 2018-11-09 10:37 a.m., Fox, John wrote:
> Dear Aoibheann,
> 
> There is no specific Anova() method for "glmmTMB" objects, so the default method is invoked. This won't work because of the structure of "glmmTMB" models. I think that ideally one would want two tables of Wald tests of fixed effects, one for the conditional nonzero part of the model and one for the zero-inflation part of the model. 
> 
> This seems to me of sufficient interest that I'll look into writing "glmmTMB" methods for Anova() and for the linearHypothesis() function in the car package, on which Anova() depends. I can't promise, however, when I'll get to this.
> 
> Best,
>  John
> 
> --------------------------------------
> John Fox, Professor Emeritus
> McMaster University
> Hamilton, Ontario, Canada
> Web: socialsciences.mcmaster.ca/jfox/
> 
> 
> 
>> -----Original Message-----
>> From: R-sig-mixed-models [mailto:r-sig-mixed-models-bounces using r-
>> project.org] On Behalf Of Aoibheann Gaughran
>> Sent: Friday, November 9, 2018 10:23 AM
>> To: Ben Bolker <bbolker using gmail.com>
>> Cc: r-sig-mixed-models using r-project.org
>> Subject: Re: [R-sig-ME] post hoc tests for glmmTMB
>>
>> 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="glmmTM
>>> B"))>
>>>>> 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
>>>>>
>>>>>         [[alternative HTML version deleted]]
>>>>>
>>>>> _______________________________________________
>>>>> R-sig-mixed-models using r-project.org mailing list
>>>>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>>>>>
>>>>
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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
>>
>> 	[[alternative HTML version deleted]]
>>
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