Dear R-Helpers

(1)
After a night's sleep, I realized why the other helpers think differently
from me.
I agree with others that it may be better to use multi-stratum model but I
was a bit surprised since they seem to think 'block' variable should *not*
be a fixed effect.

A. Others seemed to think,
"Kevin is trying to estimate 'multi-stratum' model since he is using
Error(block)"

B. I thought
"Kevin is trying to estimate a simple ANOVA model (*not* random effects
model) but did not use the right R code"

I thought so for the following reasons.
1) I looked up the book in Amazon and browsed the index using ' Search
Inside' function. It does not seem to cover random effects model.
2) The description of the book says it uses Minitab so I guessed Kevin is
getting R code from somewhere else.
3) In addition, Kevin's code looked very similar to the example code of
'aov'.
The example code of 'aov' has the following code segment involving 'block'
variable
## as a test, not particularly sensible statistically
npk.aovE <- aov(yield ~ N*P*K + Error(block), npk)
So, I guessed Kevin might have gotten his code from here. After emailing
Kevin, I found that he is using the code from 'split-plot' section
of MASS, so my guess is not that far off.

(2)
I got this new bits of information from Kevin.

The data set is from a psychological experiment and subjects are *assigned*
to one of the blocks according to their scores on a test. Subjects with the
lowest scores are assigned to block A, and highest to block E. These blocks
were *not* randomly chosen from a larger set of blocks. Then the treatment
was randomized within each 'block'.

Given this new information, I think it is okay to solve Kevin's question
simply by using
aov(Score.changes ~ Therapy + Block, data=table)
assuming the fixed effects of 'block'.

I would appreciate your correction if I am mistaken here.

======================================
T.K. (Tae-kyun) Kim
Ph.D. student
Department of Marketing
Marshall School of Business
University of Southern California
======================================

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