event.nab.2 is 0/1 and I dichotomized va to get va.2 to see if I could get geeglm to work. glm has no problem with the data but geeglm chokes. Each subject (patient.id) has at most 2 observations and more than 3/4 of the subjects have 2 observations. I have even worse problems trying to use glmmPQL from MASS and worse still trying to use lmer from lme4. But I figured a marginal model would work. (geeglm seems to work OK with most of the explanatory factors in the data set I have but a couple of them show similar problems.)
> summary(glm(event.nab.2~va.2,family=binomial(link="logit"),data=test)) Call: glm(formula = event.nab.2 ~ va.2, family = binomial(link = "logit"), data = test) Deviance Residuals: Min 1Q Median 3Q Max -0.3787 -0.3787 -0.2246 -0.2246 2.7177 Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) -2.5993 0.1804 -14.41 < 2e-16 *** va.2(84, Inf] -1.0685 0.3435 -3.11 0.00187 ** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 363.19 on 958 degrees of freedom Residual deviance: 352.28 on 957 degrees of freedom AIC: 356.28 Number of Fisher Scoring iterations: 6 summary(geeglm(event.nab.2~va.2,family=binomial(link="logit"),id=patient.id,cor="exch",data=test)) Error in geese.fit(xx, yy, id, offset, soffset, w, waves = waves, zsca, : nrow(zsca) and length(y) not match > head(test) patient.id event.nab.2 va.2 1 1 0 (-Inf,84] 2 1 0 (-Inf,84] 3 2 0 (84, Inf] 4 2 0 (84, Inf] 5 3 0 (84, Inf] 6 3 0 (84, Inf] I'm using R 2.3.1 and the latest version of geepack. I get a similar error message if I use va which is continuous. I don't know what the error message from geeglm/geese means. Rick B. ______________________________________________ R-help@stat.math.ethz.ch 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.