Journal of Causal Inference
Displaying 1 - 2 of 2
Rudolph, K. E., Williams, N. T., Miles, C. H., Antonelli, J., & Diaz, I. (2023). All models are wrong, but which are useful? Comparing parametric and nonparametric estimation of causal effects in finite samples. Journal of Causal Inference, 11(1). https://doi.org/10.1515/jci-2023-0022
Publication Date
Columbia Affiliation
View
Díaz, I., Williams, N., & Rudolph, K. E. (2023). Efficient and flexible mediation analysis with time-varying mediators, treatments, and confounders. Journal of Causal Inference, 11(1). https://doi.org/10.1515/jci-2022-0077
Publication Date
Columbia Affiliation
View