Hi all.
I have started using the mmrm package in connection with some simulation studies I am performing. I am fitting a model along the lines of :
mmrm.fit <- mmrm(
formula = CFB ~ treatweek.factor + obs.baselineweek.factor + us(week.factor | subj.id),
data = df[planned.week != 0]
)
Based on this model I will derive a complex quantity, and would like to employ bootstrapping techniques to get at confidence interval. I have been playing around with the lmeresampler pacakge, however that only works on lme4 and nlme objects.
Have you considered to implement methods for bootstrapping, og teaming up with the lmeresampler-folks making their package work on mmrm objects?
Kr, Henrik
Originally posted by @henrikibster in #314 (comment)
Hi all.
I have started using the mmrm package in connection with some simulation studies I am performing. I am fitting a model along the lines of :
mmrm.fit <- mmrm(
formula = CFB ~ treatweek.factor + obs.baselineweek.factor + us(week.factor | subj.id),
data = df[planned.week != 0]
)
Based on this model I will derive a complex quantity, and would like to employ bootstrapping techniques to get at confidence interval. I have been playing around with the lmeresampler pacakge, however that only works on lme4 and nlme objects.
Have you considered to implement methods for bootstrapping, og teaming up with the lmeresampler-folks making their package work on mmrm objects?
Kr, Henrik
Originally posted by @henrikibster in #314 (comment)