8 citations · 17 across the 8 of their papers we have counts for
12 papers · 1 filter
More power to you: Using machine learning to augment human coding for more efficient inference in text-based randomized trials
Reagan Mozer, Luke Miratrix
For randomized trials that use text as an outcome, traditional approaches for assessing treatment impact require that each document first be manually coded for constructs of intere…
Improving the Estimation of Site-Specific Effects and their Distribution in Multisite Trials
JoonHo Lee, Jonathan Che, Sophia Rabe-Hesketh +2
In multisite trials, researchers are often interested in several inferential goals: estimating treatment effects for each site, ranking these effects, and studying their distributi…
Improving instrumental variable estimators with post-stratification
Nicole E. Pashley, Luke Keele, Luke W. Miratrix
Experiments studying get-out-the-vote (GOTV) efforts estimate the causal effect of various mobilization efforts on voter turnout. However, there is often substantial noncompliance…
Designing Experiments Toward Shrinkage Estimation
Evan T. R. Rosenman, Luke Miratrix
We consider how increasingly available observational data can be used to improve the design of randomized controlled trials (RCTs). We seek to design a prospective RCT, with the in…
Is it who you are or where you are? Accounting for compositional differences in cross-site treatment variation
Benjamin Lu, Eli Ben-Michael, Avi Feller +1
Multisite trials, in which treatment is randomized separately in multiple sites, offer a unique opportunity to disentangle treatment effect variation due to "compositional" differe…
Using Simulation to Analyze Interrupted Time Series Designs
Luke Miratrix
We are sometimes forced to use the Interrupted Time Series (ITS) design as an identification strategy for potential policy change, such as when we only have a single treated unit a…