External Time-to-Event Control Data for Propensity Score Balancing

Source: R/data.R

This is a simulated dataset used to illustrate Bayesian dynamic borrowing in the case when borrowing from an external control arm with a time-to-event endpoint, where the baseline covariate distributions of the internal and external data are balanced via inverse probability weighting.

ex_tte_df

Format

ex_tte_df

A data frame with 150 rows and 9 columns:

subjid

Unique subject ID

y

Response (observed time at which the participant either had an event or was censored)

enr_time

Enrollment time

total_time

Time from study start

event

Event indicator (1: event; 0: censored)

cov1

Covariate 1, which is normally distributed around 65 with a SD of 10

cov2

Covariate 2, which is binary (0 vs. 1) with about 30% of participants having level 1

cov3

Covariate 3, which is binary (0 vs. 1) with about 40% of participants having level 1

cov4

Covariate 4, which is binary (0 vs. 1) with about 50% of participants having level 1