multiple.regression.with.ci <- function(regress.out, level=0.95)
{
################################################################
#                                                              #
#  This function takes the output from an lm                   #
#  (linear model) command in R and provides not                #
#  only the usual output from the summary command, but         #
#  adds confidence intervals for intercept and slope.          #
#                                                              #
#  This version accommodates multiple regression parameters    #
#                                                              #
################################################################
usual.output <- summary(regress.out)
t.quantile <- qt(1-(1-level)/2, df=regress.out$df)
number.vars <- length(regress.out$coefficients)
temp.store.result <- matrix(rep(NA, number.vars*2), nrow=number.vars)
for(i in 1:number.vars)
{
     temp.store.result[i,] <- summary(regress.out)$coefficients[i] +
      c(-1, 1) * t.quantile * summary(regress.out)$coefficients[i+number.vars]
}
  intercept.ci <- temp.store.result[1,]
  slopes.ci <- temp.store.result[-1,]
  output <- list(regression.table = usual.output, intercept.ci = intercept.ci,
              slopes.ci = slopes.ci)
return(output)
}