[R] function logit() vs logistic regression

[David Winsemius]

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