Exploring design effects of stepped wedge designs with baseline measurements

In the previous post, I described an incipient effort that I am undertaking with two colleagues, Monica Taljaard and Fan Li, to better understand the implications for collecting baseline measurements on sample size requirements for stepped wedge cluster randomized trials. (The three of us are on the Design and Statistics Core of the NIA IMPACT Collaboratory.) In that post, I conducted a series of simulations that illustrated the design effects in parallel cluster randomized trials derived analytically in a paper by Teerenstra et al. [Read More]

The design effect of a cluster randomized trial with baseline measurements

Is it possible to reduce the sample size requirements of a stepped wedge cluster randomized trial simply by collecting baseline information? In a trial with randomization at the individual level, it is generally the case that if we are able to measure an outcome for subjects at two time periods, first at baseline and then at follow-up, we can reduce the overall sample size. But does this extend to (a) cluster randomized trials generally, and to (b) stepped wedge designs more specifically? [Read More]