Simulation study
SE
SECONDARY
The primary aim of the simulation study was to assess whether the empirical power of testing the treatment effect in the random slopes model in (1) differed from the power specified for the original sample size calculation when mean trajectories and/or treatment effects were non-linear. The secondary aim was to assess the performance of the less restrictive analysis models described in the "Possible alternative models for analysis" section when used at the trial analysis stage, having powered the trial using the random slopes model.The general format of our simulations is as follows (see also graphical summary in Fig. Simulate previously collected data. Simulate an observational study of size Analyse previously collected data. Use the model in (5) to get estimates of Calculate sample size. Calculate a sample size, Simulate trial data. Simulate a trial of size Analyse trial data (see the "Methods of analysis for the trial" section). The treatment effect at the final time point is saved, along with its SE.Repeat 5000 times. The empirical power (along with other metrics; see the "Performance measures" section) is then calculated from the saved treatment effects and their SEs. 5000 repeats gives a Monte Carlo SE of Graphical summary of the structure of the simulation. DGM: data generating mechanism. LTFC: linear trajectories, free covariance model. FCTFC: free control-group trajectory, free covariance model. FTFC: free trajectories, free covariance modelIn the following sections, we describe the elements of the simulation study in more detail.Our simulations are loosely based on Expanded Disability Status Scale (EDSS) data from the MS-STAT trial [All simulations were run in Stata 14 [