Re: st: gradient and the inverse of the information matrix

[<kirin_guess@yahoo.com.tw>]

I have a manuscript that is exactly related to your question. The article 
also briefs some possible reasons why the score test conducted by SAS and 
STATA can be different. (See the footnote 6.)
You can download the article from:
https://docs.google.com/file/d/0B984NoKuZv46akZPeGRKcTZHekU/edit?usp=sharing

Chi-lin Tsai



-----Original Message----- 
From: Jon Mu
Sent: Wednesday, May 01, 2013 10:01 PM
To: Listserv STATA
Subject: st: gradient and the inverse of the information matrix

Hi Statalisters,

I am trying to check into the (Rao's) score (or commonly known as the 
Lagrange Multiplier) test for a model that I am working on. I got results 
from SAS already, and I want to see if those from SAS would square with the 
one produced from my own Stata codes.

They don't match, and looks like I probably made some mistakes in my Stata 
codes. For the generalized formula to get the Chi-Square statistic, I need 
to get the gradient and the inverse of the information matrix. For the 
inverse of the information matrix, I can grab from e(V) directly without any 
further calculation.

So I might've made some mistake in the gradient. I've searched through the 
voluminous Stata pdf documentation using gradient as the key word, and I was 
not able to find useful information. But I vaguely remember a while back ago 
when I was also checking into related issues, I read somewhere that the 
e(gradient) matrix is a gradient with respect to xb, not b, so I suspect 
that might be the cause. I am wondering if that's the case. If I am right on 
this, then a follow-up question is how to recover the gradient with respect 
to b since I feel there might not be a linear transformation that I can use 
to get it directly. Any input/suggestion would be appreciated.

Jun Xu, PhD
Associate Professor
Department of Sociology
Ball State University
Muncie, IN 46037
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