I am trying to perform an ANOVA on a dependent variable that has large mass on the 1 side of the (0, 1] interval. I decided to use Fractional Regression Models, as implemented in the package frm. This package seems well-suited for my problem, but I don't see how to perform model comparisons of nested frm models. Please, see data and code below.
I would like to do: anova(model1, model2) There is a function frm.ptest(model1, model2), but does not work with nested models. Are there alternatives to the frm package to perform ANOVAs on proportions (with large mass on an extreme of [0, 1])? Is there a way to model repeated measures (as in package lme4) when the dependent variable is a proportion? Data and code ------------- con <- url("http://sccn.ucsd.edu/~rapela/avshift/anovaDataFrame.RData") myData <- get(load(con)) close(con) myData <- myData[!is.na(myData$alternationRate),] y <- myData$alternationRate library(frm) model1 <- frm(y=y, x=model.matrix(~modality*condition+clusterID, data=myData)[, -1], linkfrac="logit", linkbin="logit", type="2P", inflation=1) model2 <- frm(y=y, x=model.matrix(~modality+condition+clusterID, data=myData)[, -1], linkfrac="logit", linkbin="logit", type="2P", inflation=1) # this works frm.ptest(model2, model3) # but this does not # frm.ptest(model1, model2) # # Error in frm.ptest(model1, model2) : # object 2 is nested in object 1 - no need to use the P test Thanks, Joaquin ______________________________________________ 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.