glmutli package assistance please
Hello Michael, thank you for your responses. I will have to look through the myriad of iterations of attempts at all this on this project but it seems to me that I tried that? Or tried to convert the integers to numeric and it errored out? If not I certainly will do so and let know, thank you Sir! WHP From: Michael Dewey <lists at dewey.myzen.co.uk> Sent: Thursday, November 15, 2018 7:24 AM To: Bill Poling <Bill.Poling at zelis.com>; r-sig-mixed-models at r-project.org; r-help (r-help at r-project.org) <r-help at r-project.org> Subject: Re: [R] glmutli package assistance please 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 Confidentiality Notice This message is sent from Zelis. ...{{dropped:13}}
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