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From |
"Nick Cox" <n.j.cox@durham.ac.uk> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
st: RE: prediction after y-logged regression |

Date |
Mon, 2 Jun 2008 13:29:24 +0100 |

There is a large literature on this problem, especially it seems in health economics. If you use -glm, link(log)- the predictions are in essence adjusted automatically. What you describe is a special case of smearing, which is very easy too in the case of log transformation. In my experience the results of using -glm, link(log)- and of smearing are very similar. I prefer -glm-. Nick n.j.cox@durham.ac.uk Shehzad Ali I am running a regression in which y variable is logged (semi-logarithmic). The literature suggests that in order to get an anti-logged prediction of yhat, one should proceed like this: 1. Run the regression and predict yhat, 2. Then exponentiate the predicted yhat, and finally 3. Mutiply the exponentiated predicted yhat by the mean value of residuals from the regression (otherwise known as smearing). I was wondering if there is a direct way to do it in stata or if there is any other method that experts would suggest to get anti-logged prediction. Thank you, Shehzad -- Shehzad I Ali Department of Social Policy & Social Work University of York YO10 5NG +44 (0) 773-813-0094 * * 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/ * * 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/

**Follow-Ups**:**st: RE: RE: prediction after y-logged regression***From:*"Shehzad Ali" <sia500@york.ac.uk>

**References**:**st: prediction after y-logged regression***From:*Shehzad Ali <sia500@york.ac.uk>

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