sim_data_Cox | R Documentation |

A dataset generated for illustration of the principal stratification analysis. This dataset represents the common case of non-compliance.

```
sim_data_Cox
```

## 'sim_data_Cox' A data frame with 1,000 rows and 7 columns:

- S
Principal Strata: "never taker", "complier" or "always taker"

- Z
Randomized treatment arm: 0 = control, 1 = treatment

- D
Actual treatment arm: 0 = control, 1 = treatment

- T
True outcome: event time

- C
Censor time

- delta
Event indicator. 1 means true outcome is observed; 0 means otherwise

- Y
The observed event time or censor time

The dataset represents the scenario where actual treatment might not be in compliance
with the randomized (assigned) treatment. Defiers and always-takers are ruled out, leaving two
strata, "never-taker" and "complier" randomly sampled with
probability 0.3, 0.7 respectively. The assigned treatment `Z`

is randomized
with 0.5 probability for either arm. The true event time `T`

is given by the following
Weibull-Cox distribution

- never-taker
`Y \sim Weibull-Cox(theta = 1, mu = 0.3)`

- complier
`Y \sim Weibull-Cox(theta = 1, mu = 2 - 0.6*Z)`

and the censor time `C`

is uniformly drawn between 0.5 and 2.

The exclusion restriction assumption holds for never-takers in this generated dataset.

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