replicateBE solution with interactions [General Sta­tis­tics]

posted by mittyri  – Russia, 2019-12-23 15:30 (2022 d 13:20 ago) – Posting: # 21020
Views: 10,167

Dear Nastya,

whenever possible use simple solutions, at least till the moment you must dive into mixed models galaxy ;-)

And more: interaction terms are not the same in SAS and R
take a look at method.B implementation inside replicateBE package
I just modified it a bit

library(replicateBE)
library(nlme)
alpha <- 0.05
options(contrasts=c("contr.treatment","contr.poly"))
Dataset <- rds01
Dataset$group<- factor(ifelse(as.numeric(levels(Dataset$subject))[Dataset$subject]<31, 1,2))
modB <- lme(log(PK) ~ sequence + group + sequence:group + period + period%in%group + treatment, random = ~1 | subject, na.action = na.omit, data = Dataset)

EMA.B <- summary(modB)
PE <- EMA.B$tTable["treatmentT", "Value"] # exp(PE) = 1.157275
CI <- exp(PE + c(-1, +1) * qt(1 - alpha, EMA.B$tTable["treatmentT", "DF"]) * EMA.B$tTable["treatmentT", "Std.Error"])
# CI = 1.071136 1.250340

Kind regards,
Mittyri

Complete thread:

UA Flag
Activity
 Admin contact
23,427 posts in 4,929 threads, 1,680 registered users;
50 visitors (0 registered, 50 guests [including 11 identified bots]).
Forum time: 05:50 CEST (Europe/Vienna)

No matter what side of the argument you are on,
you always find people on your side
that you wish were on the other.    Thomas Berger

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