Loh, W. W., and Ren, D. (2021).
Data-driven covariate selection for confounding adjustment by focusing on the stability of the effect estimator.
Submitted.
Preprint
| R code on GitHub
Loh, W. W., and Ren, D. (2021).
Improving causal inference of mediation analysis with multiple mediators using interventional indirect effects.
Submitted.
Preprint
Rosseel, Y., and Loh, W. W. (2021).
The “Structural-After-Measurement” (SAM) approach to SEM.
Revise and resubmit.
Preprint
Bogaert, J., Loh, W. W., and Rosseel, Y. (2021).
A small sample correction for factor score regression.
Submitted.
Loh, W. W., and Rosseel, Y. (2021).
Investigating the impact of omitted item-specific effects on causal effect estimation.
In preparation.
Loh, W. W., and Kim J.-S. (2021).
Evaluating sensitivity to classification uncertainty in subgroup effect analyses.
In preparation.
Preprint
Loh, W. W., and Vansteelandt, S. (2021).
Sensitivity analysis for unmeasured confounding using effect extrapolation.
In preparation.
Preprint
Loh, W. W., and Ren, D. (2021).
Estimating social influence in a social network using potential outcomes.
Psychological Methods. Advance online publication.
Preprint
| Paper
| R code on GitHub
Ren, D., Stavrova, O., and Loh, W. W. (2021).
Nonlinear effect of social interaction quantity on psychological well-being: Diminishing returns or inverted U?
Journal of Personality and Social Psychology. Advance online publication.
Paper
Cai, X., Loh, W. W., and Crawford, F. W. (2021).
Identification of causal intervention effects under contagion.
Journal of Causal Inference, 9(1), 9-38.
Paper
Loh, W. W., Moerkerke B., Loeys T., and Vansteelandt S. (2021).
Disentangling indirect effects through multiple mediators without assuming any causal structure among the mediators.
Psychological Methods, Advance online publication.
Preprint
| Paper
| Online supplemental materials
| R code on GitHub
Loh, W. W., Moerkerke B., Loeys T., and Vansteelandt S. (2020).
Nonlinear mediation analysis with high-dimensional mediators whose causal structure is unknown.
Biometrics, Accepted.
Paper
| R code on GitHub
Loh, W. W., Moerkerke B., Loeys T., and Vansteelandt S. (2020).
Heterogeneous indirect effects for multiple mediators using interventional effect models.
Epidemiologic Methods, 9(1).
Preprint
| Paper
| R code on GitHub
Loh, W. W., Moerkerke B., Loeys T., Poppe L., Crombez G., and Vansteelandt S. (2020).
Estimation of controlled direct effects in longitudinal mediation analyses with latent variables in randomised studies.
Multivariate Behavioral Research. 55(5), 763-785
Paper
Loh, W. W., and Vansteelandt S. (2020).
Confounder selection strategies targeting stable treatment effect estimators.
Statistics in Medicine. 40, 607-630.
Paper
| R code on GitHub
Loh, W. W., Hudgens M.G., Clemens J.D., Ali M., and Emch, M.E. (2020).
Randomization inference with general interference and censoring.
Biometrics, 76(1), 235– 245.
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
We think in terms of what would happen (potential outcomes), and what could have happened (counterfactuals). The idea of simulating potential outcomes is nicely described in this episode of the TV show Person of Interest: If-Then-Else.