A dataset generated for illustration of the principal stratification analysis. This dataset represents the common case of non-compliance.
sim_data_normal## `sim_data_normal` A data frame with 1,000 rows and 4 columns:
Principal Strata: "never taker", "complier" or "always taker"
Randomized treatment arm: 0 = control, 1 = treatment
Actual treatment arm: 0 = control, 1 = treatment
Outcome
The dataset represents the scenario where actual treatment might not be in compliance with the randomized (assigned) treatment. Defiers are ruled out, leaving three strata, "never taker", "complier" and "always taker" randomly sampled with probability 0.3, 0.2 and 0.5 respectively. The assigned treatment \(Z\) is randomized with 0.5 probability for either arm. The outcome \(Y\) is given by the following.
\(Y \sim N(3, 1)\)
\(Y \sim N(-1-Z, 0.5)\)
\(Y \sim N(1, 2)\)
The exclusion restriction assumption holds for never takers and always takers in this generated dataset.