Jarle Bjørgeengen wrote:
On May 24, 2009, at 3:34 , Frank E Harrell Jr wrote:
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).
Thanks,
if the date is normally distributed , symmetric confidence interval
should be ok , right ?
Yes; I do see a normal distribution about once every 10 years.
When plotting the individual sample , it looks normally distributed.
An appropriate qqnorm plot is a better way to check, but often the data
cannot tell you about the normality of themselves. It's usually better
to use methods (e.g., bootstrap) that do not assume normality and that
provide skewed confidence intervals if the data are skewed.
Frank
Best regards.
Jarle Bjørgeengen
--
Frank E Harrell Jr Professor and Chair School of Medicine
Department of Biostatistics Vanderbilt University
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