[R-sig-ME] [R] glmutli package assistance please
Bert Gunter
bgunter@4567 @ending from gm@il@com
Thu Nov 15 17:03:09 CET 2018
OK. Then post here but *not* on mixed models list. One or the other,
exclusive or.
-- Bert
Bert Gunter
"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Thu, Nov 15, 2018 at 7:52 AM Michael Dewey <lists using dewey.myzen.co.uk> wrote:
>
> Dear Bert
>
> Since glmulti operates on glm/lm models I think, although I agree about
> not cross-posting, that it was OK here. Perhaps I do not understand the
> full significance of mixed models though.
>
> Michael
>
> On 15/11/2018 15:43, Bert Gunter wrote:
> > Please do not cross post (see te posting guide). This should go only
> > to the mixed models list.
> >
> > -- Bert
> >
> > Bert Gunter
> >
> > "The trouble with having an open mind is that people keep coming along
> > and sticking things into it."
> > -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
> >
> > On Thu, Nov 15, 2018 at 3:47 AM Bill Poling <Bill.Poling using zelis.com> wrote:
> >>
> >> Hi, I have removed the pdf which was causing my e-mail to be blocked by moderators, my apologies.
> >>
> >> https://www.jstatsoft.org/article/view/v034i12/v34i12.pdf
> >>
> >> Original post:
> >>
> >> Hello. I am still trying to get some of the examples in this glmulti pdf to work with my data.
> >>
> >> I have sent e-mails to author addresses provided but no response or bounced back as in valid.
> >>
> >> I am not sure if this is more likely to receive support on r-help or r-sig-mixed-models, hence the double posting, my apologies in advance.
> >>
> >> I am windows 10 -- R3.5.1 -- RStudio Version 1.1.456
> >>
> >> glmulti: An R Package for Easy Automated Model Selection with (Generalized) Linear Models
> >>
> >> pdf Attached:
> >>
> >> On page 13 section 3.1 of the pdf they describe a routine to estimate the candidate models possible.
> >>
> >> Their data description:
> >> The number of levels factors have does not affect the number of candidate models, only their complexity. We use a data frame dod, containing as a first column a dummy response variable, the next 6 columns are dummy factors with three levels, and the last six are dummy covariates.
> >> To compute the number of candidate models when there are between 1 and 6 factors and 1 and 6 covariates, we call glmulti with method = "d" and data = dod. We use names(dod) to specify the names of the response variable and of the predictors. We vary the number of factors and covariates, this way:
> >>
> >>
> >> Their routine:
> >> dd <- matrix(nc = 6, nr = 6) for(i in 1:6) for(j in 1:6) dd[i, j] <- glmulti(names(dod)[1],
> >> + names(dod)[c(2:(1 + i), 8:(7 + j))], data = dod, method = "d")
> >>
> >> My data, I organized it similar to the example, Response, Factor, Factor, 5 covariates
> >>
> >> Classes 'data.table' and 'data.frame':23141 obs. of 8 variables:
> >> $ Editnumber2 : num 0 0 1 1 1 1 1 1 1 1 ...
> >> $ PatientGender : Factor w/ 3 levels "F","M","U": 1 1 2 2 2 2 1 1 1 1 ...
> >> $ B1 : Factor w/ 14 levels "Z","A","C","D",..: 2 2 3 3 2 2 2 2 2 2 ...
> >> $ SavingsReversed: num -0.139 -0.139 -0.139 -0.139 -0.139 ...
> >> $ productID : int 3 3 3 3 3 3 3 3 1 1 ...
> >> $ ProviderID : int 113676 113676 113964 113964 114278 114278 114278 114278 114278 114278 ...
> >> $ ModCnt : int 0 0 0 0 1 1 1 1 1 1 ...
> >> $ B2 : num -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 ...
> >> - attr(*, ".internal.selfref")=<externalptr>
> >>
> >> Trying to follow what they did, my routine, Editnumber2 is the response variable:
> >>
> >> dd <- matrix(nc = 2, nr = 5)
> >> for(i in 1:2) for(j in 1:5) dd[i, j] <- glmulti(names(r1)[1], names(r1)[c(2:(1 + i), 7:(6 + j))], data = r1, method = "d")
> >>
> >> The error: Error in terms.formula(formula, data = data) :
> >> invalid model formula in ExtractVars
> >>
> >> I have tried changing the numbers around but get results like this:
> >>
> >> Initialization...
> >> TASK: Diagnostic of candidate set.
> >> Sample size: 23141
> >> 2 factor(s).
> >> 2 covariate(s). <--appears to be missing 3 of the covariates for some reason?
> >> 0 f exclusion(s).
> >> 0 c exclusion(s).
> >> 0 f:f exclusion(s).
> >> 0 c:c exclusion(s).
> >> 0 f:c exclusion(s).
> >> Size constraints: min = 0 max = -1
> >> Complexity constraints: min = 0 max = -1 Your candidate set contains 250 models.
> >> Error in `[<-`(`*tmp*`, i, j, value = glmulti(names(r1)[1], names(r1)[c(2:(1 + :
> >> subscript out of bounds
> >>
> >>
> >> I hope someone can help straighten out my code, thank you.
> >>
> >>
> >> WHP
> >>
> >>
> >>
> >> Confidentiality Notice This message is sent from Zelis. ...{{dropped:13}}
> >>
> >> ______________________________________________
> >> R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
> >> https://stat.ethz.ch/mailman/listinfo/r-help
> >> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> >> and provide commented, minimal, self-contained, reproducible code.
> >
> > ______________________________________________
> > R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
> >
>
> --
> Michael
> http://www.dewey.myzen.co.uk/home.html
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