Hello!
When I am analyzing proportion data, I usually apply logistic regression
using a glm model with binomial family. For example:
m <- glm( cbind("not realized", "realized") ~ v1 + v2 , family="binomial")
However, sometimes I don't have the number of cases (realized, not
realized), but only the proportion and thus cannot compute the binomial
model. I just found out that the package car contains a function "logit"
which allows for logit transformation. Would it be possible to transform the
proportion data with this function and analyze the transformed data with a
glm with family="gaussian"?
Thank you very much
--
View this message in context:
http://r.789695.n4.nabble.com/function-logit-vs-logistic-regression-tp4646498.html
Sent from the R help mailing list archive at Nabble.com.
______________________________________________
[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.
