6 papers
Disentangling Causal Mechanisms in Conjoint Experiments Using Mediation
Michaël Aklin, Max Goplerud, Nicole E. Pashley +1
Conjoint experiments provide an attractive way to assess the role of multiple attributes simultaneously on decision-making. However, the randomization of multiple attributes preven…
Stratified Sampling for Model-Assisted Estimation with Surrogate Outcomes
Reagan Mozer, Nicole E. Pashley, Luke Miratrix
In many randomized trials, outcomes such as essays or open-ended responses must be manually scored as a preliminary step to impact analysis, a process that is costly and limiting.…
Design-based Causal Inference for Incomplete Block Designs
Taehyeon Koo, Nicole E. Pashley
Researchers often turn to block randomization to increase the precision of their inference or due to practical considerations, such as in multisite trials. However, if the number o…
Bounds on causal effects in factorial experiments with non-compliance
Matthew Blackwell, Nicole E. Pashley
Factorial experiments are ubiquitous in the social and biomedical sciences, but when units fail to comply with each assigned factors, identification and estimation of the average t…
Analysis and sample-size determination for audit experiments with binary response and application to identification of effect of racial discrimination on access to justice
Nicole Pashley, Brian Libgober, Tirthankar Dasgupta
Social scientists have increasingly turned to audit experiments to investigate discrimination in the market for jobs, loans, housing and other opportunities. In a typical audit exp…
Estimating Heterogeneous Causal Effects of High-Dimensional Treatments: Application to Conjoint Analysis
Max Goplerud, Kosuke Imai, Nicole E. Pashley
Estimation of heterogeneous treatment effects is an active area of research. Most of the existing methods, however, focus on estimating the conditional average treatment effects of…