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

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Logistic regression interpretation |

Date |
Wed, 22 Sep 2010 09:06:15 +0000 (GMT) |

--- On Tue, Sep 21, Dr. Bill Westman wrote: > > A simple logistic regression was run - outcome - Survived/Non Survived > > (1/0), with Group(Treatmeant/Control -- 1/0) & Risk(High/Low -- 1/0) > > > > The results > > > > ---------+------------- > > Survived | Odds Ratio > > ---------+------------- > > Risk | 4.790295 > > group | 2.111181 > > ---------+------------- > > > > Can I assume that odds of treatment survival were 2.1 times higher in > > the treatment Group for LOW risk patients? > > And for High Risk patients in the treatment group is the adds 4. 8 + > > 2.1 (or 7 times higher)? There are no interactions so the odds increases with a factor 2.1 when one receives the treatment regardless of whether one is in the high or low risk group (the baseline odds differs between the high and low risk group, but does not change our result). You can see this in the example below. The -margins- command is used in this example to get the odds (exp(linear predictor)) for each of the four groups. The -coefl- option is added to show how -margins stores each of these odds. The -di- commands use those odds to calculate the odds ratios again. Lets assume that group in your example is collgrad in mine, and that risk in your example is married in mine. You can see that without adding the interaction terms the odds ratio is the same for both married and unmarried people. *-------------------- begin example --------------------- sysuse nlsw88, clear gen byte baseline = 1 logit union i.married i.collgrad baseline, or nocons margins, exp(exp(xb())) over(married collgrad) post coefl di _b[0bn.married#1.collgrad]/_b[0bn.married#0bn.collgrad] di _b[1.married#1.collgrad]/_b[1.married#0bn.collgrad] *-------------------- end example ------------------------ (For more on examples I sent to the Statalist see: http://www.maartenbuis.nl/example_faq ) > - Also - Is the command > > listcoef, help percent > > indicating that the odds of survival are 111% higher for > Treatment group? Yes, and you could have seen that directly from the output of your -logit- command. If something changes by a factor 2 it increases 100%, and if something changes by a factor .7 then it decreases 30%. The general rule to move from a ratio to a percentage is (ratio - 1) * 100%. You found an odds ratio of 2.11, so the odds changes (2.11 - 1)*100% = 111% > and if so - is that 111% at both High/Low risk Levels? Yes, as I explained above. 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/

**Follow-Ups**:**Re: st: Logistic regression interpretation***From:*"Dr. Bill Westman" <webicky@gmail.com>

**References**:**Re: st: Logistic regression interpretation***From:*"Dr. Bill Westman" <webicky@gmail.com>

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