Hi all, I am trying to plot the one-sided confidence limits for the regression line. It seems it is ok to use predict function to compute the two sided confidence limits. Does any one know a easy way to compute the one sided confidence limits? Thank you very much in advance. Hannah [[alternative HTML version deleted]]
David Winsemius
2013-Jan-14 05:17 UTC
[R] One sided confidence limits for the regression line
On Jan 13, 2013, at 8:19 PM, li li wrote:> Hi all, > I am trying to plot the one-sided confidence limits for the regression > line. > It seems it is ok to use predict function to compute the two sided > confidence > limits. Does any one know a easy way to compute the one sided confidence > limits?Hypotheses can be "one-sided" or "two-sided". Except for the confidence intervals around observations of 0 in count data, I'm not sure what you mean by a "one-sided confidence interval". My uncertainty certainly increases when you talk about such around regression line estimates. -- David Winsemius Alameda, CA, USA
On 01/14/2013 05:19 PM, li li wrote:> Hi all, > I am trying to plot the one-sided confidence limits for the regression > line. > It seems it is ok to use predict function to compute the two sided > confidence > limits. Does any one know a easy way to compute the one sided confidence > limits?Essentially just multiply the "lack of confidence" by 2. E.g. for 95% one-sided confidence use 90% two-sided confidence limits (and choose the limit that you're interested in). E.g.: set.seed(42) x <- seq(0,10,length=101) y <- 1.5 + 2.5*x + rnorm(101,0,5) fit <- lm(y ~ x) pfit <- predict(fit,interval="confidence",level=0.90) plot(x,y) lines(x,pfit[,"fit"]) lines(x,pfit[,"upr"],col="red") You are then, for any given x value, 95% confident that the true mean of "Y" lies *below* the corresponding y-value on red curve that was plotted. cheers, Rolf Turner