I have a data set that I am attempting to analyse in R and I am relatively new to the environment.
My full data set contains 7 subjects (represented by Subject), that all receive 3 treatments (environmental conditions, represented by Altitude) and are measured 10 times within each treatment. Each participant received each treatment in a different order, represented The measurements are power (from a treadmill, represented by Power) during repeated-sprint efforts (represented by Sprint). An example:
I also have characteristics about each subject that may influence their power effort, including weight, capacity tests and age. I am interested in the effect of each Environment on the Sprint results, plus the effect of order on the Power.
I believe a linear mixed model, with subject as a random effect, is an appropriate tool to investigate my dataset. I have attempted this using the following line:
alt.model = lmer(Power ~ Sprint + Altitude + VO2max + (1|Subject), data=ALTMM)
However, I don't think this accounts for each individual sprint. How do I represent this?