5 papers
Two fully specified Bayes factors for hypothesis testing and sensitivity analysis in process tracing
Matias López, Jake Bowers, Daniel Gajardo Cooper
Fairfield and Charman (2022) propose using a Bayes factor to summarize process tracing evidence, but they require researchers to specify the probability of evidence by hand, and th…
Detecting Where Effects Occur by Testing Hypotheses in Order
Jake Bowers, David Kim, Nuole Chen
Experimental evaluations of public policies often randomize a new intervention within many sites or blocks. After an overall statistically significant result is reported, the natur…
Sequential Sensitivity Analysis for Multiple Assumptions: A Framework for Understanding Racial Disparity in Police Use of Force
Thomas Leavitt, Jake Bowers, Luke Miratrix
Inferring racial discrimination in police use of force -- the average causal effect of civilian race on use of force -- requires two assumptions about policing prior to potential u…
Randomization Tests for Distributions of Individual Treatment Effects via Combined Rank Statistics
David Kim, Yongchang Su, Jake Bowers +1
What proportion of treated units actually benefited from an experimental intervention? What is the median or the largest individual treatment effect? This paper develops methods fo…
A p-value for Process Tracing and other N=1 Studies
Matias Lopez, Jake Bowers
We introduce a method for calculating \(p\)-values to test causal hypotheses in qualitative research \emph{a la} process tracing. As in an experiment, our \(p\)-value tells us how…