6 papers
Bayesian Nonparametrics for Principal Stratification with Continuous Post-Treatment Variables
Dafne Zorzetto, Antonio Canale, Fabrizia Mealli +2
Principal stratification provides a causal inference framework for investigating treatment effects in the presence of a post-treatment variable. Principal strata play a key role in…
Difference-in-Differences in the Presence of Unknown Interference
Fabrizia Mealli, Javier Viviens
The stable unit treatment value (SUTVA) is a crucial assumption in the Difference-in-Differences (DiD) research design. It rules out hidden versions of treatment and any sort of in…
Do Test Scores Help Teachers Give Better Track Advice to Students? A Principal Stratification Analysis
Andrea Ichino, Fabrizia Mealli, Javier Viviens
Every year, over one million EU students choose a secondary school track based on teacher recommendations, yet little evidence shows this yields optimal assignments. Using Dutch da…
Causal Inference when Intervention Units and Outcome Units Differ
Georgia Papadogeorgou, Zhaoyan Song, Guido Imbens +1
We study causal inference in settings characterized by interference with a bipartite structure. There are two distinct sets of units: intervention units to which an intervention ca…
Principal stratification with continuous treatments and continuous post-treatment variables
Joseph Antonelli, Minxuan Wu, Fabrizia Mealli +2
Principal stratification (PS) is a commonly used approach for understanding the mechanisms through which a treatment affects an outcome. The goal of this work is to extend the PS f…
Evaluating causal effects on time-to-event outcomes in an RCT in Oncology with treatment discontinuation
Veronica Ballerini, Björn Bornkamp, Alessandra Mattei +3
In clinical trials, patients may discontinue treatments prematurely, breaking the initial randomization and, thus, challenging inference. Stakeholders in drug development are gener…