Related Experiment Video
Updated: May 31, 2026

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
Incorporation of historical data in the analysis of randomized therapeutic trials
Charlotte Rietbergen1, Irene Klugkist, Kristel J M Janssen
1Utrecht University, Department of Methodology and Statistics, Heidelberglaan 1, 3584 CS Utrecht, The Netherlands. c.rietbergen@uu.nl
Abstract:
Historical studies provide a valuable source of information for the motivation and design of later trials. Bayesian techniques offer possibilities for the quantitative inclusion of prior knowledge within the analysis of current trial data. Combining information from previous studies into an informative prior distribution is, however, a delicate case. The power prior distribution is a tool to estimate the effect of an intervention in a current study sample, while accounting for the information provided by previous research. In this study we evaluate the use of the power prior distribution, illustrated with data from a large randomized clinical trial on the effect of ST-wave analysis in intrapartum fetal monitoring. We advocate the use of a power prior distribution with pre-specified fixed study weights based on differences in study characteristics. We propose obtaining a ranking of the historical studies via expert elicitation, based on relevance for the current study, and specify study weights accordingly.
Related Concept Videos
Clinical Trials
There are four phases in a clinical trial. A phase one...
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Clinical Trials: Overview
Blinding
Introduction To Survival Analysis
The primary goal of survival analysis is to estimate survival time—the time until a...
Comparing the Survival Analysis of Two or More Groups
