[R] glmutli package assistance please

[Michael Dewey]

Dear Bill

I am not sure what is going on here but I notice that 2 of your 
covariates are numeric and 3 integer. What happens if you make them all 
numeric?

Michael

On 15/11/2018 11:46, Bill Poling 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
> 
> 
> 
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-- 
Michael
http://www.dewey.myzen.co.uk/home.html