How long in Stata does it take to perform estimate one -logit- model?
A couple points on your SAS code. You are using probability weights
in your Stata code but SAS is using frequency weights. Using the
Stata auto data set the following code SAS returns:
1178 proc logistic data=auto descending;
1179 class foreign ;
1180 model foreign =mpg ;
1181 weight price;
1182 run;
Analysis of Maximum Likelihood Estimates
Standard Wald
Parameter DF Estimate Error Chi-Square
Pr > ChiSq
Intercept 1 -3.8587 0.0143 73208.6299
<.0001
mpg 1 0.1478 0.000661 50063.9741
<.0001
which is equivalent to the Stata code
. logit fore mpg [fw = price], nolog
Logistic regression Number of obs = 456229
LR chi2(1) = 61231.77
Prob > chi2 = 0.0000
Log likelihood = -251056.48 Pseudo R2 = 0.1087
------------------------------------------------------------------------------
foreign | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
mpg | .1478456 .0006608 223.75 0.000 .1465505 .1491407
_cons | -3.858749 .0142614 -270.57 0.000 -3.8867 -3.830797
------------------------------------------------------------------------------
r; t=0.05 14:31:39
I don't know if changing the weights this will make your code run faster.
Also, the default technique in SAS is IRLS. Stata uses Newton-Raphson.
At least in a couple of examples, changing the technique to NR did
increase the time.
