Table 4 Simulation parameters and estimands for different scenarios in simulation study 1. For all scenarios, we set α = 0, βtrt = 3, βep = 1, βM = 1, \({\upsigma}_{\upmu}^2=5\) and \({\upsigma}_{\upvarepsilon}^2=5\)
From: Independence estimators for re-randomisation trials in multi-episode settings: a simulation study
| Â | Parameters | Estimand values | ||||||
|---|---|---|---|---|---|---|---|---|
Scenario | βTRTxEP | βTRTxM | γ | δ | \({\upbeta}_E^{AB}\) | \({\upbeta}_P^{AB}\) | \({\upbeta}_E^{PB}\) | \({\upbeta}_P^{PB}\) |
Scenario 1: Constant treatment effect | 0 | 0 | 0 | 0 | 3 | 3 | 3 | 3 |
Scenario 2: Treatment effect varies across episode | 1.5 | 0 | 0 | 0 | 3.5 | 3.38 | 3.5 | 3.38 |
Scenario 3: Treatment effect varies across patients with different values of Mi | 0 | 3 | 0 | 0 | 5 | 4.5 | 5 | 4.5 |
Scenario 4: Treatment effect carries forward | 0 | 0 | 1 | 0 | 3 | 3 | 3.33 | 3.25 |
Scenario 5: Treatment becomes less effective on re-use | 0 | 0 | 0 | -3 | 2.5 | 2.63 | 2 | 2.25 |
Scenario 6: Treatment effect varies across episodes, across patients with different values of Mi, carries forward, and becomes less effective on re-use | 1,5 | 3 | 1 | -3 | 5 | 4.5 | 4.83 | 4.38 |