From: Ted Harding <Ted.Harding_at_manchester.ac.uk>

Date: Sun, 13 Jul 2008 21:59:21 +0100 (BST)

> [...]

*>
*

> The quotation is attributed to the late Carl Sagan who

*> seemed to have used it as a strawman argument , see
*

*> http://oyhus.no/AbsenceOfEvidence.html.
*

E-Mail: (Ted Harding) <Ted.Harding_at_manchester.ac.uk> Fax-to-email: +44 (0)870 094 0861

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Received on Sun 13 Jul 2008 - 21:03:39 GMT

Date: Sun, 13 Jul 2008 21:59:21 +0100 (BST)

On 13-Jul-08 19:53:47, Johannes Huesing wrote:

> Frank E Harrell Jr <f.harrell@vanderbilt.edu> [Sun, Jul 13, 2008 at

*> 08:07:37PM CEST]:
*

>> (Ted Harding) wrote: >>> On 13-Jul-08 13:29:13, Frank E Harrell Jr wrote: >>>> [...] >>>> A large P-value means nothing more than needing more data. No >>>> conclusion is possible. Please read the classic paper Absence of >>>> Evidence is not Evidence for Absence. >>>

> [...]

>> >> It's real. Full text is available to all: >> http://www.bmj.com/cgi/content/full/311/7003/485

> The quotation is attributed to the late Carl Sagan who

This citation of Sagan, and the link therein to Sagan quotes:

http://en.wikiquote.org/wiki/Carl_Sagan

are interesting, as far as they go. However, I disagree with the proof ("by conditional probability") that absence of evidence is evidence of absence.

Definition 1 is disputable. But, whether one agrees with it or not, Definition 2 does not correspond to my interpretation of "absence of evidence". If A is evidence for B (in terms of P(B|A) etc.), this means that if we *know* that A is the case, or that not-A is the case, then we can say something about P(B). But "absence of evidence", in my interpretation (which I believe is right for the statistical context of "non-significant P-values"), means that we do not know about A: we do not have enough information.

That proof needs to be discussed in terms of the available evidence for A!

The proof is, basically, given in terms of a 2-valued logic where every term is either TRUE or FALSE. In the real world we have at least a third possible value: UNKNOWN (or, as R would put it, NA).

Even if you accept (Definition 1) that

"A is evidence for B" == P(B|A) > P(B|not-A)

what can you possibly say about P(B|NA) (other than that it is NA itself)?

Best wishes to all,

Ted.

E-Mail: (Ted Harding) <Ted.Harding_at_manchester.ac.uk> Fax-to-email: +44 (0)870 094 0861

Date: 13-Jul-08 Time: 21:59:16 ------------------------------ XFMail ------------------------------ ______________________________________________R-help_at_r-project.org mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Received on Sun 13 Jul 2008 - 21:03:39 GMT

Archive maintained by Robert King, hosted by
the discipline of
statistics at the
University of Newcastle,
Australia.

Archive generated by hypermail 2.2.0, at Sun 13 Jul 2008 - 23:31:48 GMT.

*
Mailing list information is available at https://stat.ethz.ch/mailman/listinfo/r-help.
Please read the posting
guide before posting to the list.
*