[R] Regression slope confidence interval

[Renaud Lancelot]

Why not use vcov() and the normal approximation ?

 > ctl <- c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14)
 > trt <- c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69)
 > group <- gl(2,10,20, labels=c("Ctl","Trt"))
 > weight <- c(ctl, trt)
 > lm.D9 <- lm(weight ~ group)
 >
 > cbind(estimate = coef(lm.D9),
+       lower = coef(lm.D9) - 1.96 * diag(vcov(lm.D9)),
+       upper = coef(lm.D9) + 1.96 * diag(vcov(lm.D9)))
             estimate      lower      upper
(Intercept)    5.032  4.9369482  5.1270518
groupTrt      -0.371 -0.5611037 -0.1808963

To address your needs, it might also be possible to write a method for 
the generic of intervals() in package nlme.

Best,

Renaud

Christian Hennig a écrit :
> Hi list,
> 
> is there any direct way to obtain confidence intervals for the regression
> slope from lm, predict.lm or the like?
> (If not, is there any reason? This is also missing in some other statistics
> softwares, and I thought this would be quite a standard application.)
> I know that it's easy to implement but it's for
> explanation to people who faint if they have to do their own
> programming...
> 
> Christian
> 
> *** --- ***
> Christian Hennig
> University College London, Department of Statistical Science
> Gower St., London WC1E 6BT, phone +44 207 679 1698
> chrish at stats.ucl.ac.uk, www.homepages.ucl.ac.uk/~ucakche
> 
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