Assume following probit model:
$y_i$ = $\phi$($\beta_0$+$\beta_1x_1$+$\beta_2x_1^2$+$\beta_3d_1$+$\beta_4d_2$)
where $d_1$ and $d_2$ are dummies
or in Stata:
probit y_i x1 xsq d1 d2
Now I want to predict the probabilities $P(\hat{y_i} = 1)$ for each observation x. This seems very simple but I keep failing to program it in Stata.
I tried:
predict pr, xb
But this gives me values greater than 1.
Any ideas?
Best Answer
This is on the face of it a Stata question, but there is a statistical confusion at its core. Here is wrong and right syntax for what you want exemplified.
As the help explains (just read
help probit postestimation
), the default forpredict
afterprobit
is to give predicted probabilities, and that is what you want. By insisting onxb
, you got the linear predictor. You can get what you want by pushing your predictions through the cumulative standard normal (in Statanormal()
) but just using the default gets you there directly. In essence you want a back-transformation to the probability scale, but that is so common a need that Stata (and presumably all good statistical software) provides it directly.