My guess is that this combination of variables produces separation in
the data: Too many (all?) of the response 1's are in at level of VAR3,
and the 0's are at the other level (or vice versa).
HTH,
Simon.
On Sat, 2007-12-29 at 18:39 -0500, Charles Willis wrote:> Hello,
>
> I am trying to run the APE program COMPAR.GEE with a model containing a
> categorical response variable and a mixture of continuous and categorical
> independent variables. The model runs when I have categorical (binary)
> response and two continuous independent variables (VAR1 and VAR2), but when
> I include a categorical (binary) independent variable (VAR3), I receive the
> following output with an error:
>
> Beginning Cgee S-function, @(#) geeformula.q 4.13 98/01/27
> running glm to get initial regression estimate
> (Intercept) VAR1 VAR2 VAR3
> -2.656607e+01 -3.110687e-15 -1.582172e-16 5.313214e+01
> "Error in gee(RESPONSE ~ VAR1 + VAR2 + VAR3, c(1, 1, 1, 1, 1, :
> Cgee: error: logistic model for probability has fitted value very close
to
> 1.
> estimates diverging; iteration terminated.
> In addition: Warning message:
> In glm.fit(x = X, y = Y, weights = weights, start = start, etastart >
etastart, :
> algorithm did not converge"
>
> The input is the following model:
>
> compar.gee(RESPONSE ~ VAR1 + VAR2 + VAR3, data = subset1, family >
"binomial", phy = prunedtree1)
>
> I have set all of the categorical data as factors and designated the family
> as "binomial". I don't know what else to do and the error
message is not
> clear to me. If anyone can interpret this error message and/or knows how to
> run a compar.gee with a mixed set of categorical and continuous variable, I
> would be greatly appreciative for your advice.
>
> Thank you,
> Charlie
>
>
>
>
--
Simon Blomberg, BSc (Hons), PhD, MAppStat.
Lecturer and Consultant Statistician
Faculty of Biological and Chemical Sciences
The University of Queensland
St. Lucia Queensland 4072
Australia
Room 320 Goddard Building (8)
T: +61 7 3365 2506
email: S.Blomberg1_at_uq.edu.au
Policies:
1. I will NOT analyse your data for you.
2. Your deadline is your problem.
The combination of some data and an aching desire for
an answer does not ensure that a reasonable answer can
be extracted from a given body of data. - John Tukey.