English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

I examine the problem of treatment choice when a planner observes (i)covariates that describe each member of a population of interest and (ii) theoutcomes of an experiment in which subjects randomly drawn from this populationare randomly assigned to treatment groups within which all subjects receive thesame treatment. Covariate data for the subjects of the experiment are notavailable. The optimal treatment rule is to divide the population intosubpopulations whose members share the same covariate value, and then to choosefor each subpopulation a treatment that maximizes its mean outcome. However theplanner cannot implement this rule. I draw on my work on nonparametric analysisof treatment response to address the planner's problem.

Treatment Choice in Heterogeneous Populations Using Experiments without Covariate Data (Invited Paper)