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
______________________________________________
[email protected] 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.
