Mean as intercept; model matrices [🇷 for BE/BA]
dear Elmaestro,
So far we still cannot figure out why the intercept is not the mean of lnY. However, you put Subj as one of regressors in your lm() functions. In Chow & Liu's model, the S(i,k) is the intersubject residuals of Subj i on Sequence k, not Subj itself. Could this be the reason that these two models might be different? What we use in bear with your example is like the following:
So far we still cannot figure out why the intercept is not the mean of lnY. However, you put Subj as one of regressors in your lm() functions. In Chow & Liu's model, the S(i,k) is the intersubject residuals of Subj i on Sequence k, not Subj itself. Could this be the reason that these two models might be different? What we use in bear with your example is like the following:
Snot <- lm(lnY~Trt+Subj:Seq+Per+Seq)
for a 2x2x2 ABE. It works o.k..❝ Snot = lm(lnY~Trt+Subj+Seq+Per) ## seems to be standard syntax in
❝ 1. Chow & Liu's model specification is
❝ lnY = Mean + S(i,k) + P(j) + F(j,k) + C(j-1,k) + E(i,j,k)
—
All the best,
-- Yung-jin Lee
bear v2.9.2:- created by Hsin-ya Lee & Yung-jin Lee
Kaohsiung, Taiwan https://www.pkpd168.com/bear
Download link (updated) -> here
All the best,
-- Yung-jin Lee
bear v2.9.2:- created by Hsin-ya Lee & Yung-jin Lee
Kaohsiung, Taiwan https://www.pkpd168.com/bear
Download link (updated) -> here
Complete thread:
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