Time-to-Event Simulation Data

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.

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