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}}
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}} > > ______________________________________________ > R-help at 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
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 at 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 at 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.
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 at 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 at 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 at 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