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From |
Austin Nichols <austinnichols@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Interpretation of log transformed variables in logistic regression? |

Date |
Fri, 6 Feb 2009 11:22:03 -0500 |

Jason Davis <jason_davis@umail.ucsb.edu>: A one-unit increase in log income is a 172% increase in income, which you estimate increases the odds of birth fivefold (a one-unit increase in log income increases log odds by 1.68 so a one-percent increase in income, or increase in log income of .01, increases log odds by .0168). If the odds of birth are .0204 at mean income, a one-percent increase in income increases them to .0207 or so, according to your estimates. You have bigger problems--income is not exogenous, so an exogenous increase in income might in fact have a very different causal impact on the odds of birth than the one you estimate. Perhaps even a negative impact, rather than a positive one. On Fri, Feb 6, 2009 at 10:19 AM, Jason Davis <jason_davis@umail.ucsb.edu> wrote: > I can use some help with this one. I have run a multivariate logistical > regression with log transformed continuous variables, non-transformed > continous variables, and some categorical variables. The DV is birth outcome > in a given year (yes/no) and the IV of interest is income (log transformed). > The results are in odds ratios. My confusion is how do I interpret the odds > ratio of the log transformed continous variable. Specifically, the odds > ratio of log income is 5.4. If I back transform this I get 1.68. This does > not seem right, as a $1 increase in income would raise the odds of giving > birth in a given year by 68%. This would mean $1,000 raise would increase > the odds by 0.68*1000 or a 680% increase in the odds of giving birth. Any > suggestions would be greatly appreciated. * * 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/

**Follow-Ups**:**Re: st: Interpretation of log transformed variables in logistic regression?***From:*Jason Davis <jason_davis@umail.ucsb.edu>

**References**:**st: Interpretation of log transformed variables in logistic regression?***From:*Jason Davis <jason_davis@umail.ucsb.edu>

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