On May 24, 2009, at 4:42 , Frank E Harrell Jr wrote:
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.
Is it not true that the students-T (qt(... and so on) confidence
intervals is quite robust against non-normality too ?
A teacher told me that, the students-T symmetric confidence intervals
will give a adequate picture of the variability of the data in this
particular case.
Best rgds
Jarle Bjørgeengen
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