Loh, W. W., Moerkerke B., Loeys T., and Vansteelandt S. (2019). Disentangling indirect effects through multiple mediators whose causal structure is unknown.
Under review

Loh, W. W., Moerkerke B., Loeys T., and Vansteelandt S. (2019). Interventional effect models for multiple mediators.
Paper on arXiv
R code on GitHub

Loh, W. W., Moerkerke B., Loeys T., Poppe L., Crombez G., and Vansteelandt S. (2019). Estimation of controlled direct effects in longitudinal mediation analyses with latent variables in randomised studies.
Multivariate Behavioral Research. Accepted for publication.

Loh, W. W., Hudgens M.G., Clemens J.D., Ali M., and Emch, M.E. (2019). Randomization inference with general interference and censoring.
Biometrics. Accepted Author Manuscript.
Paper
R code on GitHub

Loh, W. W., Richardson, T. S., and Robins, J. M. (2017). An apparent paradox explained.
Statistical Science, 32(3), 356-361.
Paper

Rigdon, J., Loh, W. W., and Hudgens, M. G. (2017). Response to comment on 'Randomization inference for treatment effects on a binary outcome'.
Statistics in Medicine, 36(5), 876-880.
Paper
R package

Loh, W. W., and Richardson, T. S. (2015). A finite population likelihood ratio test of the sharp null hypothesis for compliers.
In Thirty-First Conference on Uncertainty in Artificial Intelligence.
Paper
R package

Loh, W. W., and Richardson, T. S. (2013). A finite population test of the sharp null hypothesis for compliers.
In UAI Workshop on Approaches to Causal Structure Learning, 15 July, Bellevue, Washington.
Paper