[Rd] Problem with confint function
John Fox
jfox at mcmaster.ca
Fri Feb 11 19:53:32 CET 2011
Dear Kino,
The confidence intervals that you've computed yourself are based on the Wald
statistic, while confint() computes confidence intervals based on the
likelihood-ratio statistic, by profiling the likelihood (see ?confint and
click on the link for confint.glm). Basing confidence intervals on the
likelihood is more computationally intensive but should be more accurate.
I hope this helps,
John
--------------------------------
John Fox
Senator William McMaster
Professor of Social Statistics
Department of Sociology
McMaster University
Hamilton, Ontario, Canada
http://socserv.mcmaster.ca/jfox
> -----Original Message-----
> From: r-devel-bounces at r-project.org [mailto:r-devel-bounces at r-
> project.org] On Behalf Of Kino Aguilar
> Sent: February-11-11 1:26 PM
> To: R-devel at r-project.org
> Subject: [Rd] Problem with confint function
>
> Hi,
>
> I am currently doing logistic regression analyses and I am trying to get
> confidence intervals for my partial logistic regression coefficients.
> Supposing I am right in assuming that the formula to estimate a 95% CI
> for a log odds coefficient is the following:
>
> log odds - 1.96*SE to log odds + 1.96*SE
>
> then I am not getting the right CI.
>
> For instance, this is a summary of my model:
> Estimate Std. Error z value Pr(>|z|)
> (Intercept) -0.06106 0.29808 -0.205 0.8377
> pSusSD 0.21184 0.36886 0.574 0.5658
> pBenSD 1.20255 0.52271 2.301 0.0214 *
> pBarSD -0.08654 0.48749 -0.178 0.8591
> pSevSD 0.99759 0.44795 2.227 0.0259 *
>
> And this is are the corresponding CI when I call the confint function:
> 2.5 % 97.5 %
> (Intercept) -0.6548023 0.5264357
> pSusSD -0.4980888 0.9733975
> pBenSD 0.2665235 2.3495259
> pBarSD -1.0695945 0.8740359
> pSevSD 0.1877044 1.9747499
>
> Utilizing the formula I mentioned above, the correct CI for pSusSD would
> actually be:
> > .21184-1.96*.36886
> [1] -0.5111256
> > .21184+1.96*.36886
> [1] 0.9348056
>
> That is:
> 2.5 % 97.5 %
> pSusSD -0.5111256 0.9348056
>
> I am wondering if there is a bug in the code or if there is another way
> to calculate a 95% CI for a logistic regression coefficient that I am
> not aware of?
>
> Thanks!
>
> --
> All the best!,
> ~Joaquin A. Aguilar A. - aka Kino
>
> [[alternative HTML version deleted]]
>
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