[R] standard error of Binary logistic regression coefficient.

[Joshua Wiley]

Hi,

Just to extend the excellent suggestions, if you are interested in the
odds ratio, you can just use exp():

#Odds Ratio
exp(fit4$coefficients)

#Confidence interval around OR
exp(confint(fit4))

To give you an idea graphically of the log odds (or logit) look at:

p <- seq(0, 1, by = .001)
plot(y = log(p / (1 - p) ), x = p, type = "l")

Cheers,

Josh

On Tue, Jul 27, 2010 at 8:40 AM, Bessy <piglet630 at hotmail.com> wrote:
>
> 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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>
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>



-- 
Joshua Wiley
Ph.D. Student, Health Psychology
University of California, Los Angeles
http://www.joshuawiley.com/