tte_sim_df {beastt} | R Documentation |
Time-to-Event Simulation Data
Description
This is an example of output from a simulation study that investigates the
operating characteristics of inverse probability weighted Bayesian dynamic
borrowing for the case with a time-to-event outcome. This output was generated
based on the time-to-event simulation template. For this simulation study, only the
degree of covariate imbalance (as indicated by population
) and the
marginal treatment effect were varied.
Usage
tte_sim_df
Format
tte_sim_df
A data frame with 18 rows and 7 columns:
- population
Populations defined by different covariate imbalances
- marg_trt_eff
Marginal treatment effect
- true_control_surv_prop
True control survival probability at time t=12 months on the marginal scale
- reject_H0_yes
Probability of rejecting the null hypothesis in the case with borrowing
- no_borrowing_reject_H0_yes
Probability of rejecting the null hypothesis without borrowing
- pwr_prior
Vector of IPW power priors as distributional objects
- mix_prior
Vector of mixture priors (i.e., the robustified IPW power priors) as distributional objects