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From |
"Scott Merryman" <scott.merryman@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Replicating a sas loop in stata results in very slow computation time.... |

Date |
Thu, 10 Apr 2008 14:52:27 -0500 |

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.

**References**:**st: Replicating a sas loop in stata results in very slow computation time....***From:*PatrickT@umac.mo

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