Message-ID: <17EB5185-8D21-42F4-B423-794355812D72@bjorgeengen.net>
Date: 2009-05-25T07:05:35Z
From: Jarle Bjørgeengen
Subject: sciplot question
In-Reply-To: <4A195CF3.90109@vanderbilt.edu>
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.
Best rgds
Jarle Bj?rgeengen