[R] standard error of Binary logistic regression coefficient.

[Achim Zeileis]

On Tue, 27 Jul 2010, John Sorkin wrote:

> Do not worry about the SE. The SE listed on the output is the SE of the log odds. You can use the estimate (beta) and SE from the listing to compute a confidence interval (CI)as follows:
> CI exp(beta-1.96*SE) to exp(beta-1.96*SE)

The standard errors can be computed by using the vcov() method:
   sqrt(diag(vcov(glm_object)))

Confidence intervals can be computed using the confint() method:
   confint(glm_object)

hth,
Z

> John
> John Sorkin
> Chief Biostatistics and Informatics
> Univ. of Maryland School of Medicine
> Division of Gerontology and Geriatric Medicine
> JSorkin at grecc.umaryland.edu
> -----Original Message-----
> From: Bessy <piglet630 at hotmail.com>
> To:  <r-help at r-project.org>
>
> Sent: 7/27/2010 11:40:33 AM
> Subject: [R] standard error of Binary logistic regression coefficient.
>
>
> Dear all,
>
> I am struggling with the calculation of standard error of the coefficient in
> Binary logistic regression analysis.
>
> I built a binary logsitic regression model as follows and got confused since
> the calculation of standard error of coefficients of X1, X2 and X3 are not
> the same as the Linear regression.
>
>> fit4 <-glm(Y~X1+X2+X3,data=d4,family=binomial("logit"))
> Warning message:
> In glm.fit(x = X, y = Y, weights = weights, start = start, etastart =
> etastart,  :
>  fitted probabilities numerically 0 or 1 occurred
>> summary(fit4)
>
> Call:
> glm(formula = Y ~ X1 + X2 + X3, family = binomial("logit"), data = d4)
>
> Deviance Residuals:
>          Min             1Q         Median             3Q            Max
> -1.641483e+00  -8.421161e-05   0.000000e+00   1.349398e-03   1.417550e+00
>
> Coefficients:
>               Estimate     Std. Error  z value Pr(>|z|)
> (Intercept) -10.1534523  10.8397717 -0.93669 0.348921
> X1            0.3312469   0.3007324  1.10147 0.270693
> X2            0.1808757   0.1069222  1.69166 0.090711 .
> X3            5.0874665   5.0820163  1.00107 0.316792
> ---
> Signif. codes:  0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1
>
> (Dispersion parameter for binomial family taken to be 1)
>
>    Null deviance: 91.4954278  on 65  degrees of freedom
> Residual deviance:  5.8129055  on 62  degrees of freedom
> AIC: 13.812906
>
> Number of Fisher Scoring iterations: 12
>
>
> Could somebody suggest the calculation of standard error of X1, X2 and X3 in
> the output of my model, please?
>
> Any suggestions will be really appreciated.
>
> Kind Regards
>
> Bessy
>
> -- 
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