brm_simulate_outline: Start a simulated dataset
In brms.mmrm: Bayesian MMRMs using 'brms'

brm_simulate_outline

R Documentation

Start a simulated dataset

Begin creating a simulated dataset.

brm_simulate_outline(
  n_group = 2L,
  n_subgroup = NULL,
  n_patient = 100L,
  n_time = 4L,
  rate_dropout = 0.1,
  rate_lapse = 0.05
)

`n_group`	Positive integer of length 1, number of treatment groups.
`n_subgroup`	Positive integer of length 1, number of subgroup levels. Set to `NULL` to omit the subgroup entirely.
`n_patient`	Positive integer of length 1. If `n_subgroup` is `NULL`, then `n_patient` is the number of patients per treatment group. Otherwise, `n_patient` is the number of patients per treatment group per subgroup. In both cases, the total number of patients in the whole simulated dataset is usually much greater than the `n_patients` argument of `brm_simulate_outline()`.
`n_time`	Positive integer of length 1, number of discrete time points (e.g. scheduled study visits) per patient.
`rate_dropout`	Numeric of length 1 between 0 and 1, post-baseline dropout rate. A dropout is an intercurrent event when data collection for a patient stops permanently, causing the outcomes for that patient to be missing during and after the dropout occurred. The first time point is assumed to be baseline, so dropout is there. Dropouts are equally likely to occur at each of the post-baseline time points.
`rate_lapse`	Numeric of length 1, expected proportion of post-baseline outcomes that are missing. Missing outcomes of this type are independent and uniformly distributed across the data.