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A simulated dataset for demonstrating propensity score weighting methods in survival analysis with a binary treatment.
simdata_bin
A data frame with 1000 observations and 8 variables:
Continuous covariate (standard normal).
Binary covariate (0/1).
Treatment group: "A" or "B". Distribution is approximately 40:60.
Observed follow-up time (event or censoring), range 0-20.
Event indicator: 1 = event observed, 0 = censored.
The data were generated with the following characteristics:
Treatment assignment depends on X1, X2, and B1 via logistic model.
Survival times follow Weibull distributions with group-specific scales (group A has better survival than group B).
Censoring times follow an exponential distribution depending on X1 and B1.
Administrative censoring occurs at time 20.
Overall censoring rate is approximately 30
simdata_multi for a dataset with 4 treatment groups.
simdata_multi
data(simdata_bin) head(simdata_bin) table(simdata_bin$Z)
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