Jarle Bjørgeengen wrote:
Great,
thanks Manuel.
Just for curiosity, any particular reason you chose standard error , and
not confidence interval as the default (the naming of the plotting
functions associates closer to the confidence interval .... ) error
indication .
- Jarle Bjørgeengen
On May 24, 2009, at 3:02 , Manuel Morales wrote:
You define your own function for the confidence intervals. The function
needs to return the two values representing the upper and lower CI
values. So:
qt.fun <- function(x) qt(p=.975,df=length(x)-1)*sd(x)/sqrt(length(x))
my.ci <- function(x) c(mean(x)-qt.fun(x), mean(x)+qt.fun(x))
Minor improvement: mean(x) + qt.fun(x)*c(-1,1) but in general confidence
limits should be asymmetric (a la bootstrap).
I'm not sure how NAs are handled.
Frank
lineplot.CI(x.factor = dose, response = len, data = ToothGrowth,
ci.fun=my.ci)
Manuel
On Fri, 2009-05-22 at 18:38 +0200, Jarle Bjørgeengen wrote:
Hi,
I would like to have lineplot.CI and barplot.CI to actually plot
confidence intervals , instead of standard error.
I understand I have to use the ci.fun option, but I'm not quite sure
how.
Like this :
qt(0.975,df=n-1)*s/sqrt(n)
but how can I apply it to visualize the length of the student's T
confidence intervals rather than the stdandard error of the plotted
means ?
--
http://mutualism.williams.edu
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