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




-- 
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Charles G. Willis
Department of Organismic and Evolutionary Biology
22 Divinity Ave Cambridge MA 02139
HP (857) 488-2506
WP (617) 496-3890
cgwillis@oeb.harvard.edu
http://www.people.fas.harvard.edu/%7Ecgwillis/
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