2 papers
stat.ME2024
A Kernel Test for Causal Association via Noise Contrastive Backdoor Adjustment
Robert Hu, Dino Sejdinovic, Robin J. Evans
Causal inference grows increasingly complex as the number of confounders increases. Given treatments , confounders and outcomes , we develop a non-parametric method to te…
stat.ME2024
Combining experimental and observational data through a power likelihood
Xi Lin, Jens Magelund Tarp, Robin J. Evans
Randomized controlled trials are the gold standard for causal inference and play a pivotal role in modern evidence-based medicine. However, the sample sizes they use are often too…