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

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

125
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
125
Blinding01:11

Blinding

2.4K
Blinding is a commonly used method of not telling participants which treatment a subject is receiving. Blinding is a critical part of a randomized control trial or RCT. It reduces the bias that affects the results. In an RCT, blinding is used in the form of a placebo. A placebo effect occurs when untreated subjects falsely believe they have received the treatment and report improved symptoms. A placebo or a dummy treatment is administered to subjects to negate the bias caused by such an effect.
2.4K
Study Design in Statistics01:15

Study Design in Statistics

8.0K
A study design is a set of techniques that allow a researcher to collect and analyze data from different variables defined for a specific research problem. Statistics is commonly for effective study design and more robust experiments,
Does aspirin reduce the risk of heart attacks? Is one brand of fertilizer more effective at growing roses than another? Is fatigue as dangerous to a driver as the influence of alcohol? Questions like these are answered using randomized experiments with proper...
8.0K
Confounding in Epidemiological Studies01:27

Confounding in Epidemiological Studies

162
Confounding in statistical epidemiology represents a pivotal challenge, referring to the distortion in the perceived relationship between an exposure and an outcome due to the presence of a third variable, known as a confounder. This variable is associated with both the exposure and the outcome but is not a direct link in their causal chain. Its presence can lead to erroneous interpretations of the exposure's effect, either exaggerating or underestimating the true association. This...
162
Study Designs in Epidemiology01:20

Study Designs in Epidemiology

211
Epidemiological study designs are fundamental tools for investigating the distribution, determinants, and control of health conditions in populations. They help researchers understand the relationships between exposures and outcomes, and they broadly fall into two categories: "observational" and "experimental" studies.
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and...
211
Randomized Experiments01:13

Randomized Experiments

6.9K
The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
6.9K

You might also read

Related Articles

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

Sort by
Same author

Comparing global and community indicators of safety and peace.

African journal of psychological assessment·2026
Same author

Prevalence and Impact of Disorders of Gut-Brain Interaction in France: Results From the Rome Foundation Global Epidemiology Study.

Neurogastroenterology and motility·2026
Same author

Triple-stack geostatistical modeling for urban injury: Integrating grids, built environment, and Poisson kriging for pedestrian fatalities in Cali, Colombia.

Health informatics journal·2026
Same author

Prevalence and Burden of Fatigue Across Disorders of Gut-Brain Interaction: Results From the Rome Foundation Global Epidemiology Study.

Alimentary pharmacology & therapeutics·2026
Same author

Association of Air Pollution With Brain Health: A Cross-Sectional Analysis of Adults Living in Canada.

Stroke·2026
Same author

FEV1 is a major prognostic factor in diverse heart failure populations: findings from the Global Heart Failure registry.

ESC heart failure·2026

Related Experiment Video

Updated: Jun 23, 2025

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

14.4K

Accounting for center-level effects in multicenter randomized controlled trials.

Shofiqul Islam1, Shrikant I Bangdiwala2,3

  • 1Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Canada. shofiqul.islam@phri.ca.

Trials
|June 17, 2024
PubMed
Summary

Analyzing multicenter randomized controlled trials (RCTs) requires careful consideration of center effects. Accounting for these effects as fixed or random can impact hypothesis testing and error rates in trial analysis.

More Related Videos

Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment
08:36

Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment

Published on: April 19, 2024

491
Author Spotlight: Exploring the Impact of Reduced Resistance Exercise Volume on Metabolic Health
06:13

Author Spotlight: Exploring the Impact of Reduced Resistance Exercise Volume on Metabolic Health

Published on: December 1, 2023

1.1K

Related Experiment Videos

Last Updated: Jun 23, 2025

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

14.4K
Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment
08:36

Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment

Published on: April 19, 2024

491
Author Spotlight: Exploring the Impact of Reduced Resistance Exercise Volume on Metabolic Health
06:13

Author Spotlight: Exploring the Impact of Reduced Resistance Exercise Volume on Metabolic Health

Published on: December 1, 2023

1.1K

Area of Science:

  • Clinical Trials Methodology
  • Biostatistics
  • Health Services Research

Background:

  • Multicenter randomized controlled trials (RCTs) enhance recruitment speed and population generalizability.
  • Heterogeneity in participant characteristics, site practices, and investigator expertise across centers can lead to variations in effect estimates.
  • Standard analysis often ignores center effects, but their impact on primary hypothesis testing remains unclear.

Purpose of the Study:

  • To review current practices for accounting for center effects in published RCTs.
  • To investigate the impact of different analytical approaches (ignoring, fixed effects, random effects) on hypothesis testing in multicenter RCTs.
  • To provide recommendations on when to account for center effects based on their impact on statistical power and error rates.

Main Methods:

  • Review of published multicenter RCT analyses to assess current practices regarding center effects.
  • Simulation studies using linear and logistic regression models for continuous and binary outcomes, respectively.
  • Comparison of three methods: ignoring center effects, treating centers as fixed effects, and treating centers as random effects.
  • Evaluation of the impact of these methods on Type I and Type II error rates.

Main Results:

  • Significant heterogeneity in effect estimates is commonly observed across centers in multicenter RCTs.
  • The choice of analytical method (ignoring, fixed, or random effects) influences Type I and Type II error rates.
  • Simulation results indicate that accounting for center effects can impact the validity of primary hypothesis tests.

Conclusions:

  • Ignoring center effects in multicenter RCTs can lead to inaccurate conclusions regarding treatment efficacy.
  • Accounting for center effects, either as fixed or random, is crucial for preserving the integrity of hypothesis testing.
  • Guidelines are provided to help researchers determine when center-level effects necessitate specific analytical adjustments.