sciplot question

Manuel Morales wrote:

On Mon, 2009-05-25 at 06:22 -0500, Frank E Harrell Jr wrote:

Jarle Bj?rgeengen wrote:

On May 24, 2009, at 4:42 , Frank E Harrell Jr wrote:

Jarle Bj?rgeengen wrote:

On May 24, 2009, at 3:34 , Frank E Harrell Jr wrote:

Jarle Bj?rgeengen 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 Bj?rgeengen
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.

Incorrect.  Try running some simulations on highly skewed data.   
You will find situations where the confidence coverage is not very  
close of the stated level (e.g., 0.95) and more situations where  
the overall coverage is 0.95 because one tail area is near 0 and  
the other is near 0.05.

The larger the sample size, the more skewness has to be present to  
cause this problem.

OK - I'm convinced. It turns out that the first change I made to  
sciplot
was to allow for asymmetric error bars. Is there an easy way (i.e.,
existing package) to bootstrap confidence intervals in R. If so, I'll
try to incorporate this as an option in sciplot.

library(Hmisc)
?smean.cl.boot