[R] geeglm error NA/NaN/Inf in 'y'

[Brant Inman]

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 <dulcalma at 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: mackay at northnet.com.au
> 
> 
> 
> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On
> Behalf Of Brant Inman
> Sent: Sunday, 2 March 2014 03:52
> To: r-help at 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 
> 
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