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From |
Maarten buis <maartenbuis@yahoo.co.uk> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: interpretation of exponentiated standardized coefficients in OLS |

Date |
Wed, 14 Apr 2010 05:35:42 -0700 (PDT) |

--- On Wed, 14/4/10, Sergi VIDAL TORRE wrote: > Suppose I have a standardized coefficient in an OLS > regression. I now (for some obscure reason) wouldlike to > eponentiate it in order to interpret the value as a > percentual change in the dependent variable (as an > odds-ratio in logisitc regression). Is is possible to > interpret the values aresulting from such a transformation > as an analogous change in percentages? As a rule, exponentiating the coefficients does _not_ lead to the interpretation of factor change in dependent variable for a unit change in the independent variable. There are exception: 1) you used a log() inside link function, this is for instance what happens when you do a logit, where the link function is the log of the odds. 2) you have log transformed the dependent variable prior to estimation your model. HOWEVER, you are now modeling the conditional geometric mean rather than the conditional arithmatic mean, this is usually _not_ what you want. Under normal circumstances you would want to use -glm- with the -log()- link, see for instance this post from earlier today: <http://www.stata.com/statalist/archive/2010-04/msg00726.html> If you are really sure you want to model the conditional geometric mean, you can look at: Roger Newson (2003) "Stata tip 1: The eform() option of regress" The Stata Journal, 3(4):445. <http://www.stata-journal.com/article.html?article=st0054> Hope this helps, Maarten -------------------------- Maarten L. Buis Institut fuer Soziologie Universitaet Tuebingen Wilhelmstrasse 36 72074 Tuebingen Germany http://www.maartenbuis.nl -------------------------- * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: interpretation of exponentiated standardized coefficients in OLS***From:*Sergi VIDAL TORRE <sergi.vidal@upf.edu>

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