Goodness of Fit statistic Tobit model - r

Question

I have estimated a Tobit model using the censReg package, along with the censReg function. Alternatively, the same Tobit model is estimated using the tobit function in the AER package.
Now, I really like to have some goodness of fit statistic, such as the Pseudo-R2. However, whenever I try to estimate this, the output returns as NA. For example:
Tobit <- censReg(Listing$occupancy_rate ~ ., left = -Inf, right = 1, data = Listing)
PseudoR2(Tobit, which = "McFadden")
[1] NA
So far, I have only seen reported Pseudo-R2's when people use Stata. Does anyone know how to estimate it in R?
Alternatively, Tobit estimates the (log)Sigma, which is basically the standard deviation of the residuals. Could I use this to calculate the R2?
All help is really appreciated.

Answer 1

You can use DescTools package to calculate PseudoR2. You have not provided any sample data. So, it is hard for me to run your model. I am using a default dataset like
library(DescTools)
r.glm <- glm(Survived ~ ., data=Untable(Titanic), family=binomial)
PseudoR2(r.glm, c("McFadden"))
For your model, you can use something like
library(AER)
data("Affairs", package = "AER")
fm.tobit <- tobit(affairs ~ age + yearsmarried + religiousness + occupation + rating,
data = Affairs)
#Create a function for pseudoR2 calculation
pseudoR2 <- function(obj) 1 - as.vector(logLik(obj)/logLik(update(obj, . ~ 1)))
pseudoR2(fm.tobit)
#>[1] 0.05258401
Or using censReg as you have used
library(censReg)
data("Affairs", package = "AER")
estResult <- censReg(affairs ~ age + yearsmarried + religiousness +
occupation + rating, data = Affairs)
summary(estResult)
pseudoR2(estResult)
#>[1] 0.05258401
You can find the details about pseudoR2 in the following link
R squared in logistic regression