Message-ID: <48D8E121.1040205@uke.uni-hamburg.de>
Date: 2008-09-23T12:29:21Z
From: Eik Vettorazzi
Subject: Coefficients, OR and 95% CL
In-Reply-To: <836786.84174.qm@web55501.mail.re4.yahoo.com>
l.mod<-glm(menarche~age,binomial)
you will get odds-ratios by exponentiating the coefficients of this
model, so
exp(coef(l.mod))
will do this job. You may notice that this will produce an "OR" for the
intercept part as well - which is not interpretable.
For the confidence intervals for this odds ratio you have to
exponentiate the borders of the "standard" confidence intervals for the
log-odds-ratios,
exp(confint(l.mod))
hth.
Luciano La Sala schrieb:
> Dear R-users,
>
> After running a logistic regression, I need to calculate OR by exponentiating the coefficient, and then I need the 95% CL for the OR as well. For the following example (taken from P. Dalaagard's book), what would be the most straightforward method of getting what I need? Could anyone enlight me please?
>
> Thank you!
> Lucho
>
>
>> summary(glm(menarche~age,binomial))
>>
>
> Call:
> glm(formula = menarche ~ age, family = binomial)
>
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -4.68654 -0.13049 -0.01067 0.09608 2.35254
>
> Coefficients:
> Estimate Std. Error z value Pr(>|z|)
> (Intercept) -17.9175 1.7074 -10.49 <2e-16 ***
> age 1.3549 0.1296 10.45 <2e-16 ***
> ---
> Signif. codes: 0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1
>
> (Dispersion parameter for binomial family taken to be 1)
>
> Null deviance: 974.31 on 703 degrees of freedom
> Residual deviance: 223.95 on 702 degrees of freedom
> (635 observations deleted due to missingness)
> AIC: 227.95
>
> Number of Fisher Scoring iterations: 9
>
>
>
>
>
>
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> and provide commented, minimal, self-contained, reproducible code.
>
--
Eik Vettorazzi
Institut f?r Medizinische Biometrie und Epidemiologie
Universit?tsklinikum Hamburg-Eppendorf
Martinistr. 52
20246 Hamburg
T ++49/40/42803-8243
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