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
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