Kenward-Roger ≥ Satterthwaite [RSABE / ABEL]

posted by Helmut Homepage – Vienna, Austria, 2019-11-08 21:57 (1122 d 23:58 ago) – Posting: # 20771
Views: 7,516

Hi PharmCat,

❝ I thought that Kenward-Roger provide the same DF as Satterthwaite's for one-dimension effects, so as CI for coefficient is one-dimension hypothesis DF should be the same, as it describes in reference paper, may be SAS make any corrections, I don't know...


Try this one:

library(replicateBE)
ds  <- substr(grep("rds", unname(unlist(data(package = "replicateBE"))),
                   value = TRUE), start = 1, stop = 5)
res <- data.frame(rds = 1:length(ds), df.Satt = NA, df.KR = NA)
for (j in seq_along(ds)) {
  res$df.Satt[j] <- method.B(option = 1, print = FALSE, details = TRUE,
                             data = eval(parse(text = ds[j])))$DF
  res$df.KR[j]   <- method.B(option = 3, print = FALSE, details = TRUE,
                             data = eval(parse(text = ds[j])))$DF
}
res[, 2:3] <- signif(res[, 2:3], 5)
print(res, row.names = FALSE)


The EMA’s Method B evaluated by lmer() of package lmerTest. Kenward-Roger’s degrees of freedom ≥ Satterthwaite’s.

Dif-tor heh smusma 🖖🏼 Довге життя Україна! [image]
Helmut Schütz
[image]

The quality of responses received is directly proportional to the quality of the question asked. 🚮
Science Quotes

Complete thread:

UA Flag
Activity
 Admin contact
22,428 posts in 4,694 threads, 1,598 registered users;
17 visitors (0 registered, 17 guests [including 13 identified bots]).
Forum time: 21:56 CET (Europe/Vienna)

Statistics is the art of never having to say you’re wrong.
Variance is what any two statisticians are at.    C.J. Bradfield

The Bioequivalence and Bioavailability Forum is hosted by
BEBAC Ing. Helmut Schütz
HTML5