Dear Thomas Lumley:
According to your suggestion I have sorted the 'newdata' by id. When I print
the results the error was still there. So I tried to sort the 'newdata' by y,
x although I don't think it make sense. The error was still there. Here it
was the part of the code:
data1=newdata[order(newdata$id),]
print("gee model:")
mfit1 <-
gee(y~x,data=data1,family=poisson(link="log"),id=id,corstr="exchangeable")
print(mfit1)
the error is still in the results:
GEE: GENERALIZED LINEAR MODELS FOR DEPENDENT DATA
gee S-function, version 4.13 modified 98/01/27 (1998)
Model:
Link: Logarithm
Variance to Mean Relation: Poisson
Correlation Structure: Exchangeable
Call:
gee(formula = y ~ x, id = id, data = data1, family = poisson(link = "log"),
corstr = "exchangeable")
Number of observations : 150
Maximum cluster size : 3
Coefficients:
(Intercept) x
1.6389 0.7619
Estimated Scale Parameter: 1.012
Number of Iterations: 1
Working Correlation[1:4,1:4]
Error in print(x$working.correlation[1:4, 1:4], digits = digits) :
subscript out of bounds
I don't know why it is. Thanks for your help.
I still attach my part of the programming. This programming you can run in R.
Thanks again.
Best regards.
Sincerely,
Cynthia Wu
--- On Sun, 9/7/08, Thomas Lumley <[EMAIL PROTECTED]> wrote:
> From: Thomas Lumley <[EMAIL PROTECTED]>
> Subject: Re: [R] an error to call 'gee' function in R
> To: "Qinglin Wu" <[EMAIL PROTECTED]>
> Cc: r-help@r-project.org
> Date: Sunday, September 7, 2008, 6:41 PM
> From the gee() help page:
>
> Data are assumed to be sorted so that observations
> on a cluster are contiguous rows for all entities in the
> formula.
>
> -thomas
>
>
> On Sun, 7 Sep 2008, Qinglin Wu wrote:
>
> > Dear List:
> >
> > I found an error when I called the 'gee'
> function. I cannot solve and explain it. There are no
> errors when I used the 'geeglm' function. Both
> functions fit the gee model. The project supervisor
> recommends me to use the 'gee' function. But I
> cannot explain to him why this error happens. Would you
> help me solve this problem? I appreciate your help.
> >
> > In this project I will use the 'gee' or
> 'geeglm' and 'glmer' to fit the simulated
> multivariate count responses. I generated the data like
> this:
> >
> > Set ¦Â0 = ¦Â1 = 1, ¦Ì0 = 3, and n = 50.
> > For each 1 ¡Ü i ¡Ü n,
> > Simulate xi from N (1, 1).
> > Simulate zi0 and zit from
> > zi0 follows i.d. Poisson (¦Ì0) ,
> > zit | xi follows i.d. Poisson (¦Ìit) , 1 ¡Ü t ¡Ü
> 3,
> > log (¦Ìit) = log(E (zit | xi)) = ¦Â0t + xi¦Â1t =
> 1+xi.
> > Let yit = zi0 + zit, 1 ¡Ü t ¡Ü 3.
> >
> > So my data frame, let me call it 'simdata',
> the first 10 rows look like this:
> > id y.1 y.2 y.3 x
> > 1 3 5 6 -0.06588626
> > 2 6 7 6 -0.08265981
> > 3 6 8 13 0.58307719
> > 4 22 21 28 2.21099940
> > 5 5 12 8 1.06299869
> > 6 8 21 24 1.47615784
> > 7 11 8 9 0.83748390
> > 8 16 15 16 1.67011313
> > 9 9 7 7 -0.14181264
> > 10 31 37 40 2.56751453
> >
> >
> > This is the longitudinal data. I will change its
> shape to analyze it.
> > The changed 'newdata' looks like this:
>
> > id x time y
> > 1 -0.06588626 1 3
> > 2 -0.08265981 1 6
> > 3 0.58307719 1 6
> > 4 2.21099940 1 22
> > 5 1.06299869 1 5
> > 6 1.47615784 1 8
> > 7 0.83748390 1 11
> > 8 1.67011313 1 16
> > 9 -0.14181264 1 9
> > 10 2.56751453 1 31
> > ...........................
> > 1 -0.06588626 2 5
> > 2 -0.08265981 2 7
> > 3 0.58307719 2 8
> > 4 2.21099940 2 21
> > 5 1.06299869 2 12
> > 6 1.47615784 2 21
> > 7 0.83748390 2 8
> > 8 1.67011313 2 15
> > 9 -0.14181264 2 7
> > 10 2.56751453 2 37
> > ...........................
> > 1 -0.06588626 3 6
> > 2 -0.08265981 3 6
> > 3 0.58307719 3 13
> > 4 2.21099940 3 28
> > 5 1.06299869 3 8
> > 6 1.47615784 3 24
> > 7 0.83748390 3 9
> > 8 1.67011313 3 16
> > 9 -0.14181264 3 7
> > 10 2.56751453 3 40
> > ...........................
> >
> >
> > My data 'y' comes from x. So their
> correlations are not independent. What does the argument
> 'corstr' mean it defined in the function. I tried
> all choices. But the error was still there. Here was the
> function I used in my programming:
> >
> > mfit1 <-
> gee(y~x,data=newdata,family=poisson(link="log"),id=id,corstr="exchangeable")
> >
> > GEE: GENERALIZED LINEAR MODELS FOR DEPENDENT DATA
> > gee S-function, version 4.13 modified 98/01/27 (1998)
> >
> > Model:
> > Link: Logarithm
> > Variance to Mean Relation: Poisson
> > Correlation Structure: Exchangeable
> >
> > Call:
> > gee(formula = y ~ x, id = id, data = newdata, family =
> poisson(link = "log"),
> > corstr = "exchangeable")
> >
> > Number of observations : 150
> >
> > Maximum cluster size : 1
> >
> > Coefficients:
> > (Intercept) x
> > 1.5849653 0.7937203
> >
> > Estimated Scale Parameter: 1.162505
> > Number of Iterations: 1
> >
> > Working Correlation[1:4,1:4]
> > Error in print(x$working.correlation[1:4, 1:4], digits
> = digits) :
> > subscript out of bounds
> >
> >
> >
> > Is this kind of data not fit for the function
> 'gee'? Because when I tested this two functions by
> using the R data 'warpbreaks' they worked perfect
> although some returned objects were different. I used the
> following to do it:
> > 1. (summary(gee(breaks ~ tension, id=wool,
> data=warpbreaks, corstr="exchangeable"))
> > 2. summary(geeglm(breaks ~ tension, id=wool,
> data=warpbreaks, corstr="exchangeable"))).
> >
> > The first one is from the example of ?gee file.
> >
> > I will attach the part of my programming as .R file.
> You can excute in R software. Thanks a lot.
> >
> >
> > I appreciate your help.
> >
> >
> > Best regards.
> >
> > Sincerely,
> > Cynthia Wu
> >
>
> Thomas Lumley Assoc. Professor, Biostatistics
> [EMAIL PROTECTED] University of Washington, Seattle
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