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 [EMAIL PROTECTED] http://www.people.fas.harvard.edu/%7Ecgwillis/ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ [[alternative HTML version deleted]] ______________________________________________ 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.
