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RE: st: An urgent request for help :-)


From   "Salvati, Jean" <JSalvati@imf.org>
To   <statalist@hsphsun2.harvard.edu>
Subject   RE: st: An urgent request for help :-)
Date   Thu, 17 Nov 2005 17:52:23 -0500

<suest> followed by <nlcom> might be relevant.

One way of storing estimation results is to use <estimates store>. The
help file for <nlcom> contains an example.

The alternative is to write a program that stores estimation results in
matrices, and then passes them to your own code for the test.

Jean Salvati

> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu 
> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of 
> Roger Newson
> Sent: Thursday, November 17, 2005 5:13 PM
> To: statalist@hsphsun2.harvard.edu
> Subject: Re: st: An urgent request for help :-)
> 
> You don't state whether these 2 regressions are estimated on 
> the same or different sets of data. If they are estimated on 
> the same set of data, then any solution will probably use 
> -suest- to create a combined covariance matrix for the 2 
> regressions. If they are from independent sets of data, then 
> the 2 covariance matrices (extracted from  the estimation 
> results) can be combined diagonally to produce a combined 
> covariance matrix. Once this combined covariance matrix is 
> produced, you can produce a row vector of the derivatives of
> 
> G=(B01-B02)/(B11-B12)
> 
> with respect to B01, B11, B02 and B12, and use this vector, 
> and the combined covariance matrix, to compute a covariance for G.
> 
> I don't know how much you know about -suest-, Stata matrices, 
> and extracting estimation results. However, -whelp matrix- 
> will introduce you to Stata matrices, -whelp suest- will 
> introduce you to -suest-, and -whelp
> estimates- will introduce you to estimation results.
> 
> Best wishes
> 
> Roger
> 
> 
> At 20:47 17/11/2005, you wrote:
> >Hello,
> >This may be a slightly basic question, but I would really 
> appreciate a 
> >solution... I have two regression estimations which I run 
> sequentially, 
> >and need to get a 95% confidence interval using coefficients 
> from both 
> >these estimations in a non-linear combination.
> >Specifically, I want to get the (delta-method estimated) 95% conf.
> >interval for the following expression:
> >
> >(B01 - B02)/(B11-B12),
> >
> >  where B01 is the intercept of the 1st regression, B02 is the 
> >intercept of the second equation, B11 is a predictor 
> coefficient of the 
> >1st equation, and B12 is a predictor coefficient of the 2nd equation.
> >
> >The models I'm running are univariate regressions, but I'd 
> appreciate a 
> >multi-variate generalization as well. My question centres around how 
> >one can store and recall estimations from previous regressions while 
> >trying to work with a non-linear combination of their coefficients.
> >
> >Thank you, and looking forward to hearing from you,
> >
> >Sincerely,
> >
> >Manasi
> >*
> >*   For searches and help try:
> >*   http://www.stata.com/support/faqs/res/findit.html
> >*   http://www.stata.com/support/statalist/faq
> >*   http://www.ats.ucla.edu/stat/stata/
> 
> 
> --
> Roger Newson
> Lecturer in Medical Statistics
> Department of Public Health Sciences
> Division of Asthma, Allergy and Lung Biology King's College London
> 
> 5th Floor, Capital House
> 42 Weston Street
> London SE1 3QD
> United Kingdom
> 
> Tel: 020 7848 6648 International +44 20 7848 6648
> Fax: 020 7848 6620 International +44 20 7848 6620
>    or 020 7848 6605 International +44 20 7848 6605
> Email: roger.newson@kcl.ac.uk
> Website: http://phs.kcl.ac.uk/rogernewson/
> 
> Opinions expressed are those of the author, not the institution.
> 
> *
> *   For searches and help try:
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> *   http://www.ats.ucla.edu/stat/stata/
> 

*
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