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dc95
2010 Aug 07
2
R: Confidence Intervals for logistic regression
...se.fit, pred$fit - 1.96 *
> pred$se.fit), ncol=2 )
>
> lines( something, plogis( ci[,1] ) )
> lines( something, plogis( ci[,2] ) )
>
>
>
> On 6 August 2010 18:39, aline uwimana <rwanuza at gmail.com> wrote:
> > Dear Troy,
> > use this commend, your will get IC95% and OR.
> >
> > logistic.model <- glm(formula =y~ x1+x2, family = binomial)
> > summary(logistic.model)
> >
> > sum.coef<-summary(logistic.model)$coef
> >
> > est<-exp(sum.coef[,1])
> > upper.ci<-exp(sum.coef[,1]+1.96*sum.coef[,2])
>...