Yeah but, no but, yeah but… [General Statistics]
I must confess that I don’t have the slightest idea what you have done here. Not surprising. Hazelnut-sized brain < walnut-sized brain. However:
❝ I was happy to look up how Chow & Liu see it; see e.g. formula 2.5.1 and 9.1.1 in the 3rd edition
❝ Here's my result with EMA's dataset II, if it is of interest:
Var.Component Ini.value Value
varWR 0.01240137 0.01211072
OK, you start with the EMA’s approach.
CV.wR <- 0.01*method.A(data = rds02, print = FALSE, details = TRUE)[["CVwR(%)"]]
cat("varwR", signif(log(CV.wR^2+1), 7), "\n")
Anything goes. (© Paul Feyerabend)
With your previous REML-code I got
0.01324648and following the FDA’s approach (intra-subject contrasts) I got
0.01298984(in Phoenix, SAS, and by my -code). Hence, I see two problems:
- Your result does not match the FDA’s approach. Your previous result is even closer (+2.0%) than the new one (–6.8%).
- Even if it would match, how would you code the FDA’s mixed model for ABE in ?
That’s the most important question.
Dif-tor heh smusma 🖖🏼 Довге життя Україна!
The quality of responses received is directly proportional to the quality of the question asked. 🚮
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