[R] standard error of Binary logistic regression coefficient.

[John Sorkin]

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)
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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