Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Controls in Experiments01:13

Controls in Experiments

9.3K
When conducting an experiment, it is crucial to have control to reduce bias and accurately measure the dependent variables. It also marks the results more reliable. Controls are elements in an experiment that have the same characteristics as the treatment groups but are not affected by the independent variable. By sorting these data into control and experimental conditions, the relationship between the dependent and independent variables can be drawn. A randomized experiment always includes a...
9.3K
Experimental Designs01:16

Experimental Designs

11.8K
An experimental design is a systematic process that allows researchers to evaluate the relationship between dependent and independent variables. There are three widely used types of experimental design - pre-experimental design, true experimental design, and quasi-experimental design. In pre-experimental design, the researcher compares the data before and after some interventions or treatments. The true-experimental design has more than one purposefully created group, a commonly measured...
11.8K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

A prematurely terminated phase 2, randomised trial to evaluate immunogenicity and reactogenicity of a single versus two-dose primary vaccination regimen of the mRNA vaccine BNT162b2 in previously SARS-CoV-2 infected children 5-11 years old (CoVacc trial).

Vaccine·2026
Same author

Impact of Information Leakage in Platform Trials With Survival Endpoints on Type I Error Control.

Pharmaceutical statistics·2026
Same author

Stage-specific drivers of clinical progression in advanced chronic liver disease.

Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association·2026
Same author

Remote Monitoring Approaches to Reduce Readmissions After Infection and Sepsis: A Randomized Clinical Trial.

JAMA network open·2026
Same author

On the Inclusion of Non-Concurrent Controls in Platform Trials With an Interim Analysis.

Statistics in medicine·2026
Same author

The use of complex clinical trials: a regulatory review.

Trials·2026
Same journal

Methods for incorporating test result information within the high-dimensional propensity score framework: application in UK electronic health record data.

BMC medical research methodology·2026
Same journal

Sparse multi-way DMDC for longitudinal classification in high dimension low sample size data.

BMC medical research methodology·2026
Same journal

Tree-based exploratory identification of predictive biomarkers in non-randomized data.

BMC medical research methodology·2026
Same journal

Comparative evaluation of interrupted time series analytical methods for healthcare quality improvement research: a Monte Carlo simulation study.

BMC medical research methodology·2026
Same journal

Methodological advances in claims-based dementia algorithms: integrating medication and clinical data for medicare populations.

BMC medical research methodology·2026
Same journal

An interpretable XGboost algorithm for predicting 30-day mortality in acute pancreatitis using routine biomarkers.

BMC medical research methodology·2026
See all related articles

Related Experiment Video

Updated: Sep 1, 2025

Influence of Step-Width Manipulation on Running Biomechanics
06:53

Influence of Step-Width Manipulation on Running Biomechanics

Published on: February 28, 2025

565

On model-based time trend adjustments in platform trials with non-concurrent controls.

Marta Bofill Roig1, Pavla Krotka1, Carl-Fredrik Burman2

  • 1Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Vienna, Austria.

BMC Medical Research Methodology
|August 15, 2022
PubMed
Summary
This summary is machine-generated.

Platform trials can improve efficiency using non-concurrent controls. Step function models offer increased power but require careful consideration of time trend assumptions to avoid bias.

Keywords:
Adding armsNon-concurrent controlsPlatform trials

More Related Videos

Sit-to-stand-and-walk from 120% Knee Height: A Novel Approach to Assess Dynamic Postural Control Independent of Lead-limb
08:24

Sit-to-stand-and-walk from 120% Knee Height: A Novel Approach to Assess Dynamic Postural Control Independent of Lead-limb

Published on: August 30, 2016

10.3K
Method to Measure Tone of Axial and Proximal Muscle
10:41

Method to Measure Tone of Axial and Proximal Muscle

Published on: December 14, 2011

17.7K

Related Experiment Videos

Last Updated: Sep 1, 2025

Influence of Step-Width Manipulation on Running Biomechanics
06:53

Influence of Step-Width Manipulation on Running Biomechanics

Published on: February 28, 2025

565
Sit-to-stand-and-walk from 120% Knee Height: A Novel Approach to Assess Dynamic Postural Control Independent of Lead-limb
08:24

Sit-to-stand-and-walk from 120% Knee Height: A Novel Approach to Assess Dynamic Postural Control Independent of Lead-limb

Published on: August 30, 2016

10.3K
Method to Measure Tone of Axial and Proximal Muscle
10:41

Method to Measure Tone of Axial and Proximal Muscle

Published on: December 14, 2011

17.7K

Area of Science:

  • Clinical Trials Methodology
  • Biostatistics
  • Pharmaceutical Research

Background:

  • Platform trials efficiently evaluate multiple experimental treatments against a common control.
  • Shared control groups enhance efficiency compared to independent trials.
  • Non-concurrent controls, used when new arms are added, can boost power but risk time-trend bias.

Purpose of the Study:

  • Assess model-based approaches for adjusting time trends with non-concurrent controls in platform trials.
  • Investigate linear and step-function time trend models for new treatment arms.
  • Evaluate type 1 error, power, bias, and RMSE for continuous/binary outcomes.

Main Methods:

  • Focused on a two-arm plus control platform trial design.
  • Applied linear and step-function models to adjust for time trends.
  • Simulated various scenarios, including equal/different time trends and additive/non-additive effects.

Main Results:

  • Step function models increase power and control type 1 error when time trends are equal and additive.
  • Results hold even with block randomization, despite deviations from a pure step trend.
  • Inflated type 1 error rates occur if time trends differ between arms or are non-additive.

Conclusions:

  • Efficiency gains from step function models with non-concurrent controls can exceed bias risks, especially in small trials.
  • Potential biases arise if time trend assumptions (equality, additivity) are violated.
  • Careful consideration of trial specifics, time trend plausibility, and result robustness is crucial.