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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 – ARCHIVED

CHAPTER SECTIONS

Experimental Designs and Randomization Schemes


Section 2

Statistical Design Considerations – ARCHIVED

Expand Contributors

Patrick J. Heagerty, PhD
Elizabeth R. DeLong, PhD
For the NIH Health Care Systems Research 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 they 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 statistical 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 choice of 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 individual is randomly assigned to receive an experimental intervention, a comparator therapy, or a placebo. There is no interaction among trial 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 individual is randomly assigned to a study condition. However, there is interaction among trial participants after randomization in 1 or more of the study conditions. Many surgical trials and behavioral trials are IRGTs. These trials 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, health system, city block, or other unit that comprises multiple patients or other participants. The groups are randomly assigned to study conditions, and there is interaction among members of the same group before and after randomization. Many trials conducted in communities, worksites, 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.

Case Example: Unit of Randomization vs Unit of Measurement

The “Time to Reduce Mortality in End-Stage Renal Disease” (TiME) trial, an NIH Collaboratory Trial, provides an example of the difference between the unit of randomization and the unit of measure typical of cluster randomized trials.

In the TiME trial, participating dialysis clinics providing care to patients with end-stage renal disease were randomly assigned to provide one of two interventions: an “extended” period of hemodialysis for a minimum of 4.25 hours 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 – ARCHIVED
  2. Statistical Design Considerations – ARCHIVED
  3. Cluster Randomized Trials – ARCHIVED
  4. Randomization Methods – ARCHIVED
  5. Choosing Between Cluster and Individual Randomization – ARCHIVED
  6. Alternative Cluster Randomized Designs – ARCHIVED
  7. Concealment and Blinding – ARCHIVED
  8. Designing to Avoid Identification Bias – ARCHIVED
  9. Additional Resources – ARCHIVED

Resources

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 ePCTs, 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

January 22, 2021: Added embedded video (change made by G. Uhlenbrauck).

July 2, 2020: Minor corrections to layout and formatting (changes made by D. Seils).

May 27, 2020: Revised the text to further describe the 3 kinds of randomized trials, added the “Essentials of ePCTS Seminar” to the Resources sidebar, added Heagerty to the contributors list, and reordered the sections of this chapter as part of the annual content update (changes made by D. Seils).

April 21, 2020: Added information about the NIH Collaboratory Workshop on the Design and Analysis of Embedded Pragmatic Trials (changes made by K. Staman).

January 16, 2019: Added a Resources box and made nonsubstantive changes to the text as part of the annual content update (changes made by D. Seils).

Published August 25, 2017

current section :

Statistical Design Considerations – ARCHIVED

  1. Introduction – ARCHIVED
  2. Statistical Design Considerations – ARCHIVED
  3. Cluster Randomized Trials – ARCHIVED
  4. Randomization Methods – ARCHIVED
  5. Choosing Between Cluster and Individual Randomization – ARCHIVED
  6. Alternative Cluster Randomized Designs – ARCHIVED
  7. Concealment and Blinding – ARCHIVED
  8. Designing to Avoid Identification Bias – ARCHIVED
  9. Additional Resources – ARCHIVED

Citation:

Heagerty PJ, DeLong ER; for the NIH Health Care Systems Research Collaboratory Biostatistics and Study Design Core. Experimental Designs and Randomization Schemes: Statistical Design Considerations – ARCHIVED. 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-randomization-schemes-top/statistical-design-considerations/. Updated July 9, 2025. DOI: 10.28929/003.

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