58 citations · 177 across the 41 of their papers we have counts for
8 papers · 1 filter
Nonparametric tests of treatment effect homogeneity for policy-makers
Oliver Dukes, Mats J. Stensrud, Riccardo Brioschi +1
Recent work has focused on nonparametric estimation of conditional treatment effects, but inference has remained relatively unexplored. We propose a class of nonparametric tests fo…
Variant Specific Treatment Effects with Applications in Vaccine Studies
Gellert Perenyi, Mats J. Stensrud
Pathogens usually exist in heterogeneous variants, like subtypes and strains. Quantifying treatment effects on the different variants is important for guiding prevention policies a…
Causal inference for N-of-1 trials
Marco Piccininni, Mats J. Stensrud, Zachary Shahn +1
The aim of personalized medicine is to tailor treatment decisions to individuals' characteristics. N-of-1 trials are within-person crossover trials that hold the promise of targeti…
Quantification of vaccine waning as a challenge effect
Matias Janvin, Mats J. Stensrud
Knowing whether vaccine protection wanes over time is important for health policy and drug development. However, quantifying waning effects is difficult. A simple contrast of vacci…
Improved bounds and inference on optimal regimes
Julien D. Laurendeau, Aaron L. Sarvet, Mats J. Stensrud
Point identification of causal effects requires strong assumptions that are unreasonable in many practical settings. However, informative bounds on these effects can often be deriv…
Optimal regimes with limited resources
Aaron L. Sarvet, Julien D. Laurendeau, Mats J. Stensrud
Policy-makers are often faced with the task of distributing a limited supply of resources. To support decision-making in these settings, statisticians are confronted with two chall…
Rejoinder to "Perspectives on `harm' in personalized medicine -- an alternative perspective"
Aaron L. Sarvet, Mats J. Stensrud
In our original article (Sarvet & Stensrud, 2024), we examine twin definitions of "harm" in personalized medicine: one based on predictions of individuals' unmeasurable response ty…
Proximal Causal Inference for Conditional Separable Effects
Chan Park, Mats Stensrud, Eric Tchetgen Tchetgen
Scientists regularly pose questions about treatment effects on outcomes conditional on a post-treatment event. However, causal inference in such settings requires care, even in per…