Treatment Choice With Trial Data: Statistical Decision Theory Should Supplant Hypothesis Testing

23Citations
Citations of this article
141Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

A central objective of empirical research on treatment response is to inform treatment choice. Unfortunately, researchers commonly use concepts of statistical inference whose foundations are distant from the problem of treatment choice. It has been particularly common to use hypothesis tests to compare treatments. Wald’s development of statistical decision theory provides a coherent frequentist framework for use of sample data on treatment response to make treatment decisions. A body of recent research applies statistical decision theory to characterize uniformly satisfactory treatment choices, in the sense of maximum loss relative to optimal decisions (also known as maximum regret). This article describes the basic ideas and findings, which provide an appealing practical alternative to use of hypothesis tests. For simplicity, the article focuses on medical treatment with evidence from classical randomized clinical trials. The ideas apply generally, encompassing use of observational data and treatment choice in nonmedical contexts.

Cite

CITATION STYLE

APA

Manski, C. F. (2019). Treatment Choice With Trial Data: Statistical Decision Theory Should Supplant Hypothesis Testing. American Statistician, 73(sup1), 296–304. https://doi.org/10.1080/00031305.2018.1513377

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free