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From |
Jeph Herrin <junk@spandrel.net> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: interpretting log transformed co-efficients |

Date |
Sun, 08 Feb 2009 14:20:52 -0500 |

You might be interested in this paper http://gking.harvard.edu/files/abs/making-abs.shtml Though not clear from the abstract, the paper devotes a lot of attention to interpreting coefficients when the dependent variable is log transformed. The authors also distribute the package -clarify- net from http://gking.harvard.edu/clarify that goes with the paper. I've never used it, but the basic idea is to use simulation to get coefficients in natural units. cheers, J Ashwin Ananthakrishnan wrote:

Hi, I'm having some trouble interpretting the linear regression co-efficients for log transformed variables. I have outcomes (such as length of stay or costs) that are not normally distributed, so I'm including the log transformed (now normal) variables as the outcome measures in linear regression models. But I'm not really sure how to interpret the resulting co-efficients. Do they represent a % change in outcome for a defined change in a predictor variable? Just for example, suppose I'm modelling length of stay against gender (male 0 female 1). Without log transformation, if I get a linear regression co-efficient of 0.6, I can say that females have a 0.6 days longer stay. But if I use log (length of stay) as the outcome and get a co-efficient 0.2 for the same linear regression model, how do I interpret this? Thanks. * * 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/

* * 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: interpretting log transformed co-efficients***From:*Ashwin Ananthakrishnan <ashwinna@yahoo.com>

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