I agree too. At the end of the day when the cows come home, no amount of 
validation will turn a nonsignificant p value to a significant value or 
turn a wrong analysis to a right one.





Frank E Harrell Jr <fharrell@virginia.edu>
Sent by: r-help-bounces@stat.math.ethz.ch
04/18/2003 12:56 PM

 
        To:     "Paul, David  A" <paulda@battelle.org>
        cc:     rhelp <r-help@stat.math.ethz.ch>
        Subject:        Re: [R] Validation of R


On Fri, 18 Apr 2003 09:50:19 -0400
"Paul, David  A" <paulda@battelle.org> wrote:

. . .
> Now, what would REALLY be nice is if some generous organization
> would pay a bunch of programmers to spend 2 - 3 years validating
> the algorithms in R, taking the FDA's CFR guidelines into account...
> That would truly be a service to everyone.
>
>
> Sincerely,
>
>   David Paul

In re-reviewing FDA guidelines there are no guidelines (either usage or 
validation guidelines) for statistical analysis software, only guidelines 
for database management software and software used in medical devices. And 
the only place where SAS is mentioned is related to data archiving using 
SAS Version 5 transport files.  That (very problematic) format is 
currently preferred by FDA but experts expect that will be replaced with 
XML in the not-too-distant future.
What is truly important is that data analysts check their work no matter 
what they are doing.

By the way, I know of an important study in which incorrect final efficacy 
event rates were reported to FDA and in the scientific literature, due to 
(what I consider) a bug that has been in SAS for 30 years: a missing value 
is considered to be less than any valid numeric value, so "IF x < y THEN 
z=1" generates z=1 when x is missing and y is not.
---
Frank E Harrell Jr              Prof. of Biostatistics & Statistics
Div. of Biostatistics & Epidem. Dept. of Health Evaluation Sciences
U. Virginia School of Medicine  http://hesweb1.med.virginia.edu/biostat

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