The following are in parody (but like all good parody correct wrt the salient features).
The musings of
Guernsey McPhearson
http://www.senns.demon.co.uk/wprose.html#Mixed
http://www.senns.demon.co.uk/wprose.html#FDA
In formal publication:
Senn, Statistical Issues in Drug Development, second edition, Chapter 14:
Multicentre Trials
Senn, The many modes of meta, Drug information journal, 34:535-549, 2000.
The second points out that in a meta analysis no one would ever consider giving both large
and small trials equal weights, and relates that to several other bits of standard
practice. The 'equal weights' notion embedded in a fixed effects model + SAS type 3 is an
isolated backwater.
Terry T.
PS. The "Devils' Drug Development Dictionary" at the same source has some gems. Three
rather random choices:
Bayesian - One who, vaguely expecting a horse and catching a glimpse of a donkey, strongly
concludes he has seen a mule.
Medical Statistician - One who won't accept that Columbus discovered America because he
said he was looking for India in the trial Plan.
Trend Towards Significance - An ever present help in times of trouble.
On 07/22/2015 06:02 PM, Rolf Turner wrote:
On 23/07/15 01:15, Therneau, Terry M., Ph.D. wrote:
<SNIP>
3. Should you ever use it [i.e. Type III SS]? No. There is a very strong
inverse
correlation between "understand what it really is" and "recommend its
use". Stephen Senn has written very intellgently on the issues.
Terry --- can you please supply an explicit citation? Ta.
cheers,
Rolf
______________________________________________
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
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.
