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From |
John Antonakis <John.Antonakis@unil.ch> |

To |
statalist@hsphsun2.harvard.edu |

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

Date |
Wed, 01 May 2013 23:22:03 +0200 |

Hi:

Also see the userwritten command -scoregrp- (available through ssc). Best, J. __________________________________________ John Antonakis Professor of Organizational Behavior Director, Ph.D. Program in Management Faculty of Business and Economics University of Lausanne Internef #618 CH-1015 Lausanne-Dorigny Switzerland Tel ++41 (0)21 692-3438 Fax ++41 (0)21 692-3305 http://www.hec.unil.ch/people/jantonakis Associate Editor The Leadership Quarterly __________________________________________ On 01.05.2013 23:01, Jon Mu wrote:

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 * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

* * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**RE: st: gradient and the inverse of the information matrix***From:*Jun Xu <mystata@hotmail.com>

**References**:**st: gradient and the inverse of the information matrix***From:*Jon Mu <mystata@hotmail.com>

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