# Repeated measures between treatment and control to assess difference and influence of time

I have been using a between-subjects repeated measures ANOVA for data of treatment effect where different subjects provide data that vary by time, i.e., each subject has a reading for avg.sit.time1, avg.sit.time2, avg.sit.time3, etc. This has allowed me to assess the influence of time on repeated measurements across subjects.

I was wondering if this is the same approach to use to examine whether there is a difference between a treatment and control group of participants with the same data structure (i.e., repeated measurements, with readings increasing over time: time1, time2, time3, etc.), or would it be better to just take the average measurements for each group and do t-tests?