# [R] sciplot question

Frank E Harrell Jr f.harrell at vanderbilt.edu
Tue May 26 04:37:32 CEST 2009

```Manuel Morales wrote:
> On Mon, 2009-05-25 at 06:22 -0500, Frank E Harrell Jr wrote:
>> Jarle Bjørgeengen wrote:
>>> 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.
>> 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

>
> BTW Jarle - to answer an earlier question, standard error is "the
> standard" in my field, ecology, and that's why it's the current default
> in sciplot.

Frank

>
> Manuel
>
>> Frank
>>
>>> Best rgds
>>> Jarle Bjørgeengen
>>>
>>>
>>

--
Frank E Harrell Jr   Professor and Chair           School of Medicine
Department of Biostatistics   Vanderbilt University

```