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From | "Roger B. Newson" <r.newson@imperial.ac.uk> |
To | statalist@hsphsun2.harvard.edu |
Subject | Re: st: obtaining confidence interval from -lincom- |
Date | Sun, 26 May 2013 15:01:13 +0100 |
I hope this helps. Best wishes Roger ReferencesNewson R. Confidence intervals and p-values for delivery to the end user. The Stata Journal 2003; 3(3): 245-269. Download from
http://www.stata-journal.com/article.html?article=st0043 Roger B Newson BSc MSc DPhil Lecturer in Medical Statistics Respiratory Epidemiology and Public Health Group National Heart and Lung Institute Imperial College London Royal Brompton Campus Room 33, Emmanuel Kaye Building 1B Manresa Road London SW3 6LR UNITED KINGDOM Tel: +44 (0)20 7352 8121 ext 3381 Fax: +44 (0)20 7351 8322 Email: r.newson@imperial.ac.uk Web page: http://www.imperial.ac.uk/nhli/r.newson/ Departmental Web page: http://www1.imperial.ac.uk/medicine/about/divisions/nhli/respiration/popgenetics/reph/ Opinions expressed are those of the author, not of the institution. On 25/05/2013 14:59, Federico Belotti wrote:
Tom, you can easily put -lincom- confidence interval into scalars using scalar ci_lb = r(estimate) + invnorm(0.025)*r(se) scalar ci_ub = r(estimate) + invnorm(0.975)*r(se) scalar list if the sample is small you could substitute invnormal() with invttail() Federico Il giorno 25/mag/2013, alle ore 15:04, Tom <tommedema@gmail.com> ha scritto:Dear list, My research supervisor told me that I can generate a marginal effects plot much like the one on page 14 of Brambor et al. (2006). [1] Note that using marginsplot in Stata 12 does not create such plot. Therefore my supervisor told me to do the following: ## code start ## * regress * reg g ipr dtflog dtflogipr i.cid, robust cap drop l_dtf cap drop l_est gen l_dtflog = . gen l_est = . * lincom * forval i = 1/61 { local dtflog = (`i'-1) / 10 lincom _b[ipr] + `dtflog' * _b[dtflogipr], level(95) * save * replace l_dtflog = `dtflog' in `i' replace l_est = r(estimate) in `i' } line l_est l_dtflog ## code end ## In short: the regression has two main independent variables ipr and dtflog and one interaction term of these two variables (dtflogipr). dtflog ranges from 0 to 6 and is looped through to see the interaction effect for certain values of dtflog. I want to make the same graph as Brambor et al. (2006), where both confidence interval borders being above or below the horizontal axis indicates a singificant interaction effect. The only problem so far seems to be that while lincom returns a confidence interval, when I do -return list- I only see the estimate in r(estimate), but I cannot retrieve the confidence interval from the list. So, how would I retrieve the confidence interval listed in the table after running -lincom- ? Tom [1]: Brambor, Thomas, William Roberts Clark, and Matt Golder. "Understanding interaction models: Improving empirical analyses." Political analysis 14.1 (2006): 63-82. Available from http://localgov.fsu.edu/readings_papers/Research%20Methods/Brambor_et_al_Multipolicative_Interactions.pdf * * 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/
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