Question

Is it difficult to calculate the sample size for a SMART?

Answer

No. In fact, in most cases it is quite easy. For the three most common primary aims in a SMART, the sample size formula/calculation is either the same one used to size a standard 2-arm RCT, or it requires only a very small and intuitive adjustment this to this calculation. 

Consider the generic prototypical SMART shown in the following schematic.

If the primary aim of the SMART is to test first-stage intervention 1 vs first-stage intervention 2 (this is the “main effect” of first-stage treatment) on an end of study outcome, then the sample size calculation is identical to the calculation in a 2-arm randomized trial.  

If, instead, the primary aim of the SMART is to test the effect of modest augmentation vs vigorous augmentation among non-responders to first-stage intervention, then the SMART’s total sample size calculation can be obtained easily in two easy steps: (1) use a standard 2-arm randomized trial calculator to get the total number of non-responders needed, (2) augment this number by the anticipated non-responder rate to get the total sample size for the SMART. 

If the primary aim of the SMART is to compare two adaptive interventions starting with different first-stage treatments, the sample size is again very easy to calculate in two steps: (1) use a standard 2-arm randomized trial calculator, (2) augment this number by the “SMART inflation factor” 

Clustered SMARTs and SMARTs with a repeated measures outcome have additional adjustment factors. And, as with any randomized trial, the study’s total sample size should be further adjusted to account for study drop-out or other reasons for missing data in the primary research outcome.

 

Events

March 15th, 2024, 3 p.m.

Wenchu Pan

April 5th, 2024, 3 p.m.

Easton Huch

April 19, 2024, 3 p.m.

Jamie Yap

LET’S STAY IN TOUCH

Join the d3center Mailing List

Keep up to date with the latest news, events, software releases, learning modules, and resources from the d3center.