activity
20152026
most citedCausal inference with misspecified exposure mappings: separating definitions and assumptions

4 citations · 9 across the 7 of their papers we have counts for

collaborators

8 papers

math.ST2026

On the Impossibility of Specification Testing of Interference Models Based on Exposure Mappings

Chao Gao, Christopher Harshaw, Fredrik Sävje +1

Researchers use interference models based on exposure mappings to facilitate estimation of causal effects in randomized experiments with interference. To test the veracity of such…

econ.EM2026

Coupling Designs for Randomized Experiments with Complex Treatments

Max Cytrynbaum, Fredrik Sävje

We describe a new family of experimental designs that extends the principle of stratified randomization to settings with continuous, constrained multivariate, and other irregular t…

stat.ME2022

A General Design-Based Framework and Estimator for Randomized Experiments

Christopher Harshaw, Fredrik Sävje, Yitan Wang

We describe a widely applicable design-based framework for drawing causal inference in randomized experiments. Causal effects are defined as linear functionals evaluated at unit-le…

stat.ME2021★ 1 cited

Optimized variance estimation under interference and complex experimental designs

Christopher Harshaw, Joel A. Middleton, Fredrik Sävje

Unbiased and consistent variance estimators generally do not exist for design-based treatment effect estimators because experimenters never observe more than one potential outcome…

stat.ME2021★ 2 cited

Randomization does not imply unconfoundedness

Fredrik Sävje

A common assumption in causal inference is that random treatment assignment ensures that potential outcomes are independent of treatment, or in one word, unconfoundedness. This pap…

math.ST2021★ 4 cited

Causal inference with misspecified exposure mappings: separating definitions and assumptions

Fredrik Sävje

Exposure mappings facilitate investigations of complex causal effects when units interact in experiments. Current methods require experimenters to use the same exposure mappings bo…

stat.ME2019

Balancing Covariates in Randomized Experiments with the Gram-Schmidt Walk Design

Christopher Harshaw, Fredrik Sävje, Daniel Spielman +1

The design of experiments involves a compromise between covariate balance and robustness. This paper provides a formalization of this trade-off and describes an experimental design…

stat.ME2015★ 2 cited

The performance and efficiency of Threshold Blocking

Fredrik Sävje

A common method to reduce the uncertainty of causal inferences from experiments is to assign treatments in fixed proportions within groups of similar units: blocking. Previous resu…