[R] Differences in output of lme() when introducing interactions

[Therneau, Terry M., Ph.D.]

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
>