I do a Tobit regression to analyze censored data. To measure the goodness of fit the authors of these papers use Efron's $R^2$. So my idea is to use this one as well.
To realize my Tobit regression, I use the
tobit() function of the
AER package which is a wrapper of the
survreg function. That works fine but I'm not able to get a $R^2$ of my model.
In a similar study before I used a logistic regression and calculated the Pseudo $R^2$ with the
Pseudo Rsquared function of the
BaylorEdPsych package which worked great. Now I'm searching a solution like that for my tobit regression.
So: How do I compute a goodness of fit measure like Efron's $R^2$ for my Tobit model in R?
I don't need a certain package, if someone could give me a R snippet of computing the measure with my model.
PS: I also tried with
VGLM from the
VGAM package but no success.....