This is a simulated dataset of 7500 units with covariates and treatment measured three times and the outcome measured at the end from a hypothetical observational study examining the effect of treatment delivered at each time point on an adverse event.
The data were generated using a simple simulation mechanism. For further details on how the dataset was built, see the code at data-raw/msmdata.R.
The dataset is provided to illustrate the features of
weightitMSM() and is not based on a realistic data-generating
process, so it should not be used as a benchmark.
For simulating realistic data with a known data-generating mechanism, consider using the simcausal package.
Format
A data frame with 7500 observations on the following 10 variables.
X1_0a count covariate measured at baseline
X2_0a binary covariate measured at baseline
A_1a binary indicator of treatment status at the first time point
X1_1a count covariate measured at the first time point (after the first treatment)
X2_1a binary covariate measured at the first time point (after the first treatment)
A_2a binary indicator of treatment status at the second time point
X1_2a count covariate measured at the second time point (after the second treatment)
X2_2a binary covariate measured at the first time point (after the first treatment)
A_3a binary indicator of treatment status at the third time point
Y_Ba binary indicator of the outcome event (e.g., death)
Examples
data("msmdata")