[R-sig-ME] Unable to standardize glmmADMB global model
Aoibheann Gaughran
gaughra at tcd.ie
Thu Aug 18 15:05:06 CEST 2016
Hi Ben,
I've manually scaled and centered the continuous variables, and just scaled
the offset terms. However, I now get the following error message when I
attempt to run the model, which appears to related to a subsetting issue?
Error in `[.data.frame`(cor_dat, start_pos + (1:x$npar), start_pos + 4 + :
undefined columns selected
The revised global model is specified as follows:
stdmod12d <- glmmadmb(field_count ~ habitat #categorical
+ season_wt #cat
+ sex #cat
+ ageclass #cat
+ z.slope #continuous, scaled and centred
+ NSEW #cat
+ z.month_fix #continuous, scaled and centred
+ z.num_fields #continuous, scaled and centred
+ habitat:ageclass
+ habitat:sex
+ offset(log(z.origarea)) #scaled
+ offset(log(z.PropAvlHab)) #scaled
+(1|animal) #repeated obs from same individual
+(1|field_id) #repeated obs in same field
,
family="nbinom",
zeroInflation=TRUE,
admb.opts=admbControl(shess=FALSE,noinit=FALSE),
debug=TRUE,
data = std_data)
On 16 August 2016 at 12:55, Ben Bolker <bbolker at gmail.com> wrote:
> You can *scale* the offsets if you like, i.e. change them by a
> multiplicative factor (thus changing the effective area unit for which
> you were modeling counts), but *centering* them doesn't make sense --
> as you've noticed.
>
> On Tue, Aug 16, 2016 at 7:40 AM, Aoibheann Gaughran <gaughra at tcd.ie>
> wrote:
> > Hi Ben,
> >
> > Im proceeding by standardizing by hand. However, I need to include
> offsets
> > in my model for origarea and PropAvlHab i.e. offset(log(z.origarea)) but
> > logging the standardized varible produced NaNs due to the presence of
> > negative numbers, ditto with z.PropAvlHab. Is there a way around this?
> Do I
> > need to also standardize the offset terms or can I leave them in their
> > unstandardized form?
> >
> > Many thanks,
> >
> > Aoibheann
> >
> > On 15 August 2016 at 15:47, Ben Bolker <bbolker at gmail.com> wrote:
> >>
> >> Hmm. Surprising/hard to diagnose.
> >>
> >> 'standardize' doesn't do anything very fancy - it standardizes the
> >> input variables as described by ?arm::standardize and *refits* the
> >> model (I've always been a little disappointed that it doesn't
> >> standardize by figuring out how to transform the *parameters*, which
> >> is straightforward in principle although it can be tricky to figure
> >> out how to deal with input variables that lead to multiple predictor
> >> variables, e.g. polynomials). I'd be curious to know what's going on,
> >> but in your place I would
> >>
> >> (1) try standardizing by hand, e.g.
> >>
> >> std_data <- transform(data,
> >> z.season.wt = scale(season.wt),
> >> ...)
> >>
> >> and refit yourself.
> >>
> >> (2) see if it happens to work with glmmTMB (a simple example does).
> >>
> >> Ben Bolker
> >>
> >>
> >>
> >>
> >> On Mon, Aug 15, 2016 at 10:37 AM, Aoibheann Gaughran <gaughra at tcd.ie>
> >> wrote:
> >> > Thanks Ben, I ran the code and got the following error and warnings:-
> >> >
> >> > Error in glmmadmb(formula = field_count ~ habitat + season_wt + c.sex
> +
> >> > :
> >> > rank of X = 16 < ncol(X) = 24
> >> > In addition: Warning messages:
> >> > 1: In log(z.PropAvlHab) : NaNs produced
> >> > 2: In glmmadmb(formula = field_count ~ habitat + season_wt + c.sex +
> :
> >> > NAs removed in constructing fixed-effect model frame: you should
> >> > probably
> >> > remove them manually, e.g. with na.omit()
> >> >
> >> >
> >> > The original PropAvlHab summary is as follows:-
> >> >
> >> >> summary(dframe1$PropAvlHab)
> >> > Min. 1st Qu. Median Mean 3rd Qu. Max.
> >> > 0.0000123 0.1123000 0.4041000 0.4078000 0.6818000 1.0000000
> >> >
> >> > Aoibheann
> >> >
> >> >
> >> >
> >> > On 15 August 2016 at 15:12, Ben Bolker <bbolker at gmail.com> wrote:
> >> >>
> >> >> 'standardize' is a function from the arm package.
> >> >>
> >> >> I've just hacked glmmADMB a little bit so this should work:
> >> >>
> >> >> library(devtools)
> >> >> install_github("bbolker/glmmADMB") ## install latest version
> >> >> library(arm)
> >> >> arm:::standardize.default(fitted_model$call)
> >> >>
> >> >>
> >> >>
> >> >> On Mon, Aug 15, 2016 at 5:06 AM, Aoibheann Gaughran <gaughra at tcd.ie>
> >> >> wrote:
> >> >> > Hello Mixed-Modellers,
> >> >> >
> >> >> > I have getting the following error message when trying to
> standardize
> >> >> > my
> >> >> > global glmmadmb model for dredging:
> >> >> >
> >> >> > Error in (function (classes, fdef, mtable) : unable to find an
> >> >> > inherited
> >> >> > method for function ‘standardize’ for signature ‘"glmmadmb"’
> >> >> >
> >> >> > Is it not possible to standardise a glmmadmb model or is the
> problem
> >> >> > with
> >> >> > the structure of the model itself?
> >> >> >
> >> >> > globalmod <- glmmadmb(field_count ~ habitat
> >> >> > #categorical - 7 levels
> >> >> > + season_wt
> >> >> > #categorial - 3 levels
> >> >> > + sex
> >> >> > #categorial - 2
> levels
> >> >> > + ageclass
> >> >> > #categorial - 3 levels
> >> >> > + slope
> >> >> > #continuous, not
> scaled
> >> >> > nor
> >> >> > centred
> >> >> > + NSEW
> >> >> > #catagorical - 4 levels
> >> >> > + month_fix
> >> >> > #continuous, not scaled
> nor
> >> >> > centred,
> >> >> > + num_fields
> >> >> > #continuous, not scaled nor centred
> >> >> > + habitat:ageclass
> >> >> > + habitat:sex
> >> >> > + offset(log(origarea))
> >> >> > + offset(log(PropAvlHab))
> >> >> > +(1|individual_id)
> >> >> > #repeated obs from same
> >> >> > individual
> >> >> > +(1|field_id)
> >> >> > #repeated obs in same
> >> >> > field,
> >> >> > family="nbinom",
> >> >> > zeroInflation=TRUE,
> >> >> > admb.opts=admbControl(shess=
> FALSE,noinit=FALSE),
> >> >> > debug=TRUE,
> >> >> > data = dframe1)
> >> >> >
> >> >> > no of observations =9220
> >> >> >
> >> >> > 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
> >> >> >
> >> >> > [[alternative HTML version deleted]]
> >> >> >
> >> >> > _______________________________________________
> >> >> > R-sig-mixed-models at r-project.org mailing list
> >> >> > https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
> >> >
> >> >
> >> >
> >> >
> >> > --
> >> > 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
>
--
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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