Improving the Analysis of Randomized Controlled Trials: a Posterior Simulation Approach

Jeffrey Mills, Gary Cornwall, Beau Sauley and Jeffrey Strawn
Additional contact information
Jeffrey Strawn: Bureau of Economic Analysis

BEA Working Papers from Bureau of Economic Analysis

Abstract: The randomized controlled trial (RCT) is the standard for establishing efficacy and tolerability of treatments. However, the statistical evaluation of treatment effects in RCTs has remained largely unchanged for several decades. A new approach to Bayesian hypothesis testing for RCTs that leverages posterior simulation methods is developed. This approach (1) employs Monte Carlo simulation to obtain exact posterior distributions with fewer restrictive assumptions than required by current standard methods, allowing for a relatively simple procedure for inference with analytically intractable models, and (2) utilizes a novel approach to Bayesian hypothesis testing.

JEL-codes: E60 (search for similar items in EconPapers)
Date: 2018-09
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.bea.gov/system/files/papers/WP2018-9.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bea:wpaper:0157

Access Statistics for this paper

More papers in BEA Working Papers from Bureau of Economic Analysis Contact information at EDIRC.
Bibliographic data for series maintained by Andrea Batch ().