On Oct 17, 2012, at 11:58 AM, swertie wrote:
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"?
If you had the total number and the row proportions, shouldn't you be
able to calculate the original numbers? If you think not then you need
to be more clear about exactly what data you do and do not have.
--
David Winsemius, MD
Alameda, CA, USA
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