ac.nz, thern...@mayo.edu
> Subject: Re: [R] Differences in output of lme() when introducing
> interactions
>
> The following are in parody (but like all good parody correct wrt the
> salient features).
> The musings of
> Guernsey McPhearson
> http://www.senns.demo
On 24/07/15 07:07, Therneau, Terry M., Ph.D. wrote:
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 publicati
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, sec
On 23/07/15 01:15, Therneau, Terry M., Ph.D. wrote:
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 pl
Hi,
In addition to Terry’s great comments below, as this subject has come up
frequently over the years, there is also a great document by Bill Venables that
is valuable reading:
Exegeses on Linear Models
http://www.stats.ox.ac.uk/pub/MASS3/Exegeses.pdf
Regards,
Marc Schwartz
> On Jul 2
"Type III" is a peculiarity of SAS, which has taken root in the world. There are 3 main
questions wrt to it:
1. How to compute it (outside of SAS). There is a trick using contr.treatment coding that
works if the design has no missing factor combinations, your post has a link to such a
descri
In-line
On 20/07/2015 15:10, angelo.arc...@virgilio.it wrote:
Dear List Members,
I am searching for correlations between a dependent variable and a
factor or a combination of factors in a repeated measure design. So I
use lme() function in R. However, I am getting very different results
depen
Dear List Members,
I am searching for correlations between a dependent variable and a
factor or a combination of factors in a repeated measure design. So I
use lme() function in R. However, I am getting very different results
depending on whether I add on the lme formula various factors comp
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