Dear R Users, I'm working on a problem where I have a multivariate response vector of counts and a continuous predictor. I've thought about doing this the same way you would do a Multvariate regression model with normally distributed data, but since these data are counts, they are probably better modeled with a Poisson distribution.
For example y1<-rpois(100,3.5) y2<-rpois(100,1.5) y3<-rpois(100,.09) x<-rnorm(100, mean=25, sd=10) dat<-data.frame(y1, y2, y3, x) #Get the Multivariate linear model assuming normality fit<-lm(cbind(y1,y2,y3)~x, data=dat) fit.0<-update(fit, ~1) #Calculate Pillai's trace for global model test anova(fit, fit.0) But, if I try this approach with glm() instead of lm(), I get the error indicating that a multivariate response vector isn't allowed in glm fit.pois<-glm(cbind(y1,y2,y3)~x, data=dat, family=poisson) Error: (subscript) logical subscript too long If anyone has experience with a multivariate Poisson response vector I would gladly appreciate any suggestions. Corey Sparks -- Corey Sparks Assistant Professor Department of Demography and Organization Studies University of Texas at San Antonio 501 West Durango Blvd Monterey Building 2.270C San Antonio, TX 78207 210-458-3166 corey.sparks 'at' utsa.edu https://rowdyspace.utsa.edu/users/ozd504/www/index.htm ______________________________________________ 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.