Related Experiment Video
Updated: Aug 12, 2026

A Clinical Trial Assessing the Safety, Efficacy, and Delivery of Olive-Oil-Based Three-Chamber Bags for Parenteral Nutrition
Published on: September 20, 2019
Intention-to-treat analysis in randomized trials: who gets counted?
1Department of Pharmaceutics, School of Pharmacy, University of Washington, Seattle 98195, USA.
Abstract:
This article discusses the rationale and implications associated with the selection and use of analysis strategies for randomized clinical trials as they relate to protocol deviations. The topics addressed specifically are the conceptual and methodologic approaches and biases of clinical efficacy and effectiveness assessment. Examples are provided that highlight the consequences of different analytic strategies, particularly regarding intention-to-treat analysis. Favored by statisticians intention-to-treat analysis seeks to answer the question, "Is it better to adopt a policy of treatment A if possible, with deviations if necessary, or a policy of treatment B if possible, with deviations if necessary?" This is a relevant question, sometimes more relevant than "Is treatment A better than treatment B?" The authors suggest that different analytic strategies may be more or less appropriate depending on the intended audience.
More Related Videos
06:55Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
08:36The Adjuvant Efficacy of Angong Niuhuang Pill in the Treatment of Viral Encephalitis: A Meta-Analysis of Randomized Controlled Trials
Published on: April 19, 2024
Related Concept Videos
Blind Procedures
Randomized Experiments
Simple randomization
Simple...
Clinical Trials
There are four phases in a clinical trial. A phase one...
Blinding
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...
Censoring Survival Data