Suppose I wish to assess reaction time of individuals before and after treatment, using R code.
Now to analyse the results if I had additional treatments, I could use repeated measurements ANOVA in R, using the aov() function. These approaches however assume that there is only one measurement of reaction time per person, per treatment.
However suppose that for each individual, we measure their reaction time 5 times before treatment and 5 times after treatment. How should I adjust the t-test or repeated measurements ANOVA to account for this?
I know I could simply average prior to analysis, but is it also possible to include all the 5 trials in the analysis in R and if so how ?
Note the data might look something like this:
Subject Treatment Time Result
Subj1 Coke Morning 15
Subj1 Coke Morning 14
Subj1 Water Morning 17
Subj1 Water Morning 20
Subj2 Coke Morning 45
Subj2 Coke Morning 46
Subj2 Water Morning 58
Subj2 Water Morning 75
Best Answer
Time to shine for
afex
(full disclosure: I am the author).There are two options on what to do:
aov.car(Result ~ 1 + Error(Subj/Treatment*Time), data)
mixed
which fits those vialme4::lmer
and obtains p-values viapbkrtest::KRmodcomp
:mixed(Result ~ Treatment*Time + (Treatment*Time|Subj), data
Note, both examples assume that
Time
has more than one level. IN case you use mixed models, it is a good idea to read something on them, see?mixed
for good starting points or search on CrossValidated.