Duncan,
Thank you for your reply. The example is in fact not ordinal (the response
variable Y is an indicator of the presence or absence of obesity). I too saw
their code snippet online where they use an ordinal GEE, but the outcome
variable is binary as can be seen from the imported data from the link I
provided. I thought that that since Y is a dichotomous outcome that the model I
proposed would be appropriate, but somehow the geeglm function thinks there is
missing data and I don't see how that can be.
Any other ideas?
Brant
On Mar 1, 2014, at 8:13 PM, Duncan Mackay <dulca...@bigpond.com> wrote:
> Hi Brant
>
> I have not got Fitzmaurice etal but from their web site it seems that you
> are trying to do ordinal GEE
>
> With GEE models particularly ordinal models you MUST get your data structure
> correct otherwise it can fail or even R can crash
>
> try
>
> f1 =
> ordgee(ordered(y) ~ factor(gender) + cage + cage2 +
> factor(gender):cage + factor(gender):cage2, id = id, data =
> muscatine2,
> waves=muscatine2$occasion, mean.link="logit",
> corstr=("unstructured"))
>
>> summary(f1)
>
> Call:
> ordgee(formula = ordered(y) ~ factor(gender) + cage + cage2 +
> factor(gender):cage + factor(gender):cage2, id = id, waves =
> muscatine2$occasion,
> data = muscatine2, mean.link = "logit", corstr = ("unstructured"))
>
> Mean Model:
> Mean Link: logit
> Variance to Mean Relation: binomial
>
> Coefficients:
> estimate san.se wald p
> Inter:0 -1.214613103 0.050571150 576.8597850 0.000000e+00
> factor(gender)1 0.115330450 0.071158497 2.6268450 1.050703e-01
> cage 0.037419375 0.013263832 7.9589357 4.785054e-03
> cage2 -0.017437692 0.003378786 26.6352422 2.457205e-07
> factor(gender)1:cage 0.007510802 0.018268075 0.1690390 6.809673e-01
> factor(gender)1:cage2 0.003860069 0.004632095 0.6944407 4.046580e-01
>
> Scale is fixed.
>
> Correlation Model:
> Correlation Structure: unstructured
> Correlation Link: log
>
> Estimated Correlation Parameters:
> estimate san.se wald p
> alpha.1 3.130702 0.1535950 415.4599 0
> alpha.2 2.408103 0.1455606 273.6921 0
> alpha.3 2.793549 0.1351264 427.3978 0
>
> Returned Error Value: 0
> Number of clusters: 4856 Maximum cluster size: 3
>
> I presume that you may have a dataset in mind to work on later
>
> you may want to check out the repolr and multgee packages as well
>
> Duncan
>
> Duncan Mackay
> Department of Agronomy and Soil Science
> University of New England
> Armidale NSW 2351
> Email: home: mac...@northnet.com.au
>
>
>
> -----Original Message-----
> From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
> Behalf Of Brant Inman
> Sent: Sunday, 2 March 2014 03:52
> To: r-help@r-project.org
> Subject: [R] geeglm error NA/NaN/Inf in 'y'
>
> R-helpers:
>
> I am getting an error when trying to fit a GEE model. Below is code
> reproducing the error.
>
> ###
> library(foreign)
> muscatine <-
> read.dta('http://www.hsph.harvard.edu/fitzmaur/ala2e/muscatine.dta')
> muscatine$gender <- as.factor(muscatine$gender)
> muscatine$y <- as.factor(muscatine$y)
> muscatine$cage <- muscatine$age - 12
> muscatine$cage2 <- muscatine$cage^2
> head(muscatine); summary(muscatine)
> muscatine2 <- na.omit(muscatine); summary(muscatine2) # Remove missing
> data
>
> # GEE model to reproduce example in Fitzmaurice, Laird, Ware book
> library(geepack)
>
> f1 <- geeglm(y ~ gender*cage + gender*cage2, id=id, data=muscatine2,
> family=binomial(link=logit),
> waves=occasion, corstr='unstructured')
> ###
>
> This gives me the following error
>
>> f1 <- geeglm(y ~ gender*cage + gender*cage2, id=id, data=muscatine2,
> + family=binomial(link=logit),
> + waves=occasion, corstr='unstructured')
> Error in lm.fit(zsca, qlf(pr2), offset = soffset) : NA/NaN/Inf in 'y'
> In addition: Warning messages:
> 1: In model.response(mf, "numeric") :
> using type = "numeric" with a factor response will be ignored
> 2: In Ops.factor(y, mu) : - not meaningful for factors
>
> ###
>
> I would tremendously appreciate any help that could explain why I am getting
> this error as I am not understanding this.
>
> Brant
>
> ______________________________________________
> R-help@r-project.org mailing list
> 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@r-project.org mailing list
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.
