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NIH Collaboratory
Living Textbook of
Pragmatic Clinical Trials

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Rethinking Clinical Trials

A Living Textbook of Pragmatic Clinical Trials

  • Design
    • What is a Pragmatic Clinical Trial?
    • Decentralized Pragmatic Clinical Trials
    • Developing a Compelling Grant Application
    • Experimental Designs and Randomization Schemes
    • Endpoints and Outcomes
    • Analysis Plan
    • Using Electronic Health Record Data
    • Building Partnerships and Teams to Ensure a Successful Trial
    • Intervention Delivery and Complexity
    • Patient Engagement
  • Data, Tools & Conduct
    • Assessing Feasibility
    • Acquiring Real-World Data
    • Assessing Fitness-for-Use of Real-World Data
    • Study Startup
    • Participant Recruitment
    • Monitoring Intervention Fidelity and Adaptations
    • Patient-Reported Outcomes
    • Clinical Decision Support
    • Mobile Health
    • Electronic Health Records–Based Phenotyping
    • Navigating the Unknown
  • Dissemination & Implementation
    • Data Sharing and Embedded Research
    • Dissemination Approaches for Different Audiences
    • Implementation
    • End-of-Trial Decision-Making
  • Ethics & Regulatory
    • Privacy Considerations
    • Identifying Those Engaged in Research
    • Collateral Findings
    • Consent, Disclosure, and Non-Disclosure
    • Data and Safety Monitoring
    • Ethical Considerations of Data Sharing in Pragmatic Clinical Trials
    • Ethics for AI and ML
    • IRB Responsibilities and Procedures

Statistical Design Considerations

CHAPTER SECTIONS

Experimental Designs and Randomization Schemes


Section 2

Statistical Design Considerations

Expand Contributors

Patrick J. Heagerty, PhD
For the NIH Pragmatic Trials Collaboratory Biostatistics and Study Design Core

Contributing Editors

Damon M. Seils, MA
Jonathan McCall, MS

Although PCTs do not necessarily require a specific statistical design approach, both the kinds of questions PCTs are designed to answer and the settings in which they take place may tend to favor certain approaches, such as cluster randomization. The nature of the interventions PCTs seek to test, which may involve healthcare delivery changes, might be better implemented through randomization at the practice, clinic, or even hospital level.

In the following sections, we examine key considerations in study design and analysis for PCTs.

Watch the video module: Choosing the Right Study Design

Three Kinds of Randomized Trials

A key design factor for PCTs is the unit of randomization. There are 3 kinds of randomized trials:

In traditional RCTs, the unit of randomization is generally the individual trial participant, and each participant is randomly assigned to receive an experimental intervention, a comparator therapy, or a placebo. There is no interaction among participants after randomization. Most drug trials are traditional RCTs.

In individually randomized group treatment trials (IRGTs), like traditional RCTs, the unit of randomization is the individual trial participant, and each participant is randomly assigned to a study condition. However, there is interaction among trial participants after randomization in one or more of the study conditions. Many surgical trials and behavioral trials are IRGTs. These trial designs are sometimes called "partially nested" or "partially clustered" designs.

In cluster randomized trials (CRTs), randomization takes place at the level of the physician, practice, hospital, healthcare system, city block, or other unit that comprises multiple patients or other participants. Each group is randomly assigned to a study condition, and there is interaction among members of the same group before and after randomization. Many trials conducted in communities, work sites, schools, and other settings are CRTs. CRTs are sometimes called "group randomized trials" or "community trials." There are 2 kinds of CRTs:

  • Parallel CRTs: In a parallel CRT, there are parallel intervention and control conditions throughout the trial with no crossover.
  • Stepped-wedge CRTs: In a stepped-wedge CRT, all groups start the trial in the control condition. The groups cross over to the intervention condition in random order and on a staggered schedule. All groups receive the intervention before the end of the trial.

In CRTs, the intervention can be applied at the individual level or the cluster level, and the outcome measurements can be taken at the individual level or the cluster level.

Case Example: Unit of Randomization vs Unit of Measurement

The Time to Reduce Mortality in End-Stage Renal Disease (TiME) trial, an NIH Pragmatic Trials Collaboratory NIH Collaboratory Trial, offers an example of the difference between the unit of randomization and the unit of measure typical of CRTs. In the TiME trial, participating dialysis clinics providing care to patients with end-stage renal disease were randomly assigned to provide 1 of 2 interventions: an “extended” period of hemodialysis or standard care. The trial was designed to evaluate whether the extended period of dialysis would be associated with better survival and quality-of-life outcomes. Thus, the unit of randomization for TiME was the dialysis clinic, but the measurements of interest were the outcomes of individual patients.

Previous Section Next Section

SECTIONS

CHAPTER SECTIONS

sections

  1. Introduction
  2. Statistical Design Considerations
  3. Cluster Randomized Trials
  4. Alternative Cluster Randomized Designs
  5. Stepped-Wedge Designs
  6. Choosing Between Cluster and Individual Randomization
  7. Covariate-Constrained Randomization
  8. Pair Matching and Stratification With Cluster Designs
  9. Concealment and Masking
  10. Designing to Avoid Identification Bias
  11. Additional Resources

Resources

What Are the Types of CRT Designs?
One-minute training module from the NIH Pragmatic Trials Collaboratory's video library. Dr. Liz Turner discusses the features of 2 types of cluster randomized trials, parallel-arm and stepped-wedge designs.

Essentials of ePCTs Seminar: 2019 AcademyHealth Annual Research Meeting
Electronic booklet from a full-day preconference seminar hosted by AcademyHealth in partnership with the NIH Collaboratory, June 1, 2019

Workshop on Design and Analysis of Embedded Pragmatic Clinical Trials
NIH Collaboratory Steering Committee Meeting, May 2, 2019. Panel discussions of challenges in the design and analysis of embedded PCTs, including measurement and data, choosing a parallel group or stepped-wedge design, and unique complications of conducting research in dynamic healthcare settings.

  • View Workshop Summary
  • View Videocast
  • View Agenda or Download Individual Presentation Slides

Linking Design to Analysis of Cluster Randomized Trials: Covariate Balancing Strategies
NIH Collaboratory Grand Rounds, February 9, 2018


Version History

March 7, 2024: Added a resource to the Resources sidebar (changes made by D. Seils).

February 21, 2024: Made minor nonsubstantive text corrections (changes made by D. Seils).

Published February 7, 2023

current section :

Statistical Design Considerations

  1. Introduction
  2. Statistical Design Considerations
  3. Cluster Randomized Trials
  4. Alternative Cluster Randomized Designs
  5. Stepped-Wedge Designs
  6. Choosing Between Cluster and Individual Randomization
  7. Covariate-Constrained Randomization
  8. Pair Matching and Stratification With Cluster Designs
  9. Concealment and Masking
  10. Designing to Avoid Identification Bias
  11. Additional Resources

Citation:

Heagerty PJ; for the NIH Pragmatic Trials Collaboratory Biostatistics and Study Design Core. Experimental Designs and Randomization Schemes: Statistical Design Considerations. In: Rethinking Clinical Trials: A Living Textbook of Pragmatic Clinical Trials. Bethesda, MD: NIH Pragmatic Trials Collaboratory. Available at: https://rethinkingclinicaltrials.org/chapters/design/experimental-designs-and-randomization-schemes/statistical-design-considerations/. Updated March 27, 2024. DOI: 10.28929/203.

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