Diachi Nozaki asked about a factorial randomized blocks ANCOVA as a possible
approach to a set of experimental data, and Al Feiveson and I responded.
It dawned on me that there is an error in my posting. I wrote that one degree of
freedom must be deducted from the ANOVA table in order to account for the use of the
covariate. Instead, I believe that one degree of freedom must be deducted from the
model in Step 2 for each degree of freedom consumed in the regression in Step 1. If
Daichi opts for a fixed-effects regression (-xi: regress response i.subject*assocvar-),
then there are 19 degrees of freedom for 20 parameters estimated: one intercept for
Subject 1 and one difference from it for each of the other nine subjects and one slope
for Subject 1 and nine differences from it. If Diachi goes with random-coefficients
regression (-generate byte k=1-, -eq intercept: k-, eq slope: assocvar-, -gllamm
response assocvar, i(subject) nrf(2) eqs(intercept slope) adapt trace allc-) then there will
be four or five parameters estimated: one population mean intercept and one variance
about that population mean, one population mean slope and one variance about that,
and optionally one covariance parameter (-gllamm- estimates the covariance by
default, but it can be toggled off).
Joseph Coveney
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