Datasets were simulated using baseline covariates (sampling with replacement) from the Effects of Aspirin in Gestation and Reproduction (EAGeR) study. Data generating mechanisms were described in our manuscript (Zhong et al. (inpreparation), Am. J. Epidemiol.). True marginal causal effects on risk difference, log risk ratio and log odds ratio scales were attached to the dataset attributes (true_rd, true_logrr,true_logor).

data(eager_sim_obs)

Format

An object of class data.frame with 200 rows and 8 columns:

sim_Y

binary, simulated outcome which is condition on all other covariates in the dataset

sim_A

binary, simulated exposure which is conditon on all other covarites expect sim_Y.

eligibility

binary, indicator of the eligibility stratum

loss_num

count, number of prior pregnancy losses

age

continuous, age in years

time_try_pregnant

count, months of conception attempts prior to randomization

BMI

continuous, body mass index

meanAP

continuous, mean arterial blood pressure

References

Schisterman, E.F., Silver, R.M., Lesher, L.L., Faraggi, D., Wactawski-Wende, J., Townsend, J.M., Lynch, A.M., Perkins, N.J., Mumford, S.L. and Galai, N., 2014. Preconception low-dose aspirin and pregnancy outcomes: results from the EAGeR randomised trial. The Lancet, 384(9937), pp.29-36.

Zhong, Y., Naimi, A.I., Kennedy, E.H., (In preparation). AIPW: An R package for Augmented Inverse Probability Weighted Estimation of Average Causal Effects. American Journal of Epidemiology

See also