Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Randomized Experiments

Randomized Experiments

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...

Blinding

Blinding

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.

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

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, controlled...

Blind Procedures

Blind Procedures

Ideally, the people who observe and record the children’s behavior are unaware of who was assigned to the experimental or control group, in order to control for experimenter bias. Experimenter bias refers to the possibility that a researcher’s expectations might skew the results of the study. Remember, conducting an experiment requires a lot of planning, and the people involved in the research project have a vested interest in supporting their hypotheses. If the observers knew which child was...

Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs

Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs

Bioequivalence experimental study designs are crucial methodologies used in evaluating and comparing the bioavailability of different drug products. These designs are categorized into various types: completely randomized, randomized block, repeated measures, cross and carry-over, and Latin square designs.Completely randomized designs involve randomly allocating treatments to all subjects participating in the experiment. This allocation is achieved by assigning unique random numbers to subjects...

Censoring Survival Data

Censoring Survival Data

Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different reasons...

You might also read

Related Articles

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

Sort by

Same author

Early Adulthood Outcomes Among Individuals With Neurologic Impairment and Technology Assistance.

Pediatrics·2026

Same author

Previable Preterm Premature Rupture of the Membranes Reaching Viability: Canadian Outcomes.

Journal of obstetrics and gynaecology Canada : JOGC = Journal d'obstetrique et gynecologie du Canada : JOGC·2026

Same author

An Empirical Comparison of Statistical Methods for Estimating Treatment Effects on EQ-5D in Randomized Clinical Trials.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research·2026

Same author

Theoretical and experimental study of the correlation between pulsed light repetition frequency and electric field measurement.

Optics letters·2026

Same author

Short- and Long-Term Healthcare Costs Attributable to Hepatitis B Among Newcomers to Ontario, Canada: A Matched Cohort Study.

Canadian journal of gastroenterology & hepatology·2026

Same author

Impacts beyond the child: A theoretical framework of pediatric economic evaluation from a family perspective.

Social science & medicine (1982)·2026

Search research articles

Related Experiment Video

Updated: Jun 4, 2026

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

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

Published on: January 8, 2020

Data withdrawal in randomized controlled trials: Defining the problem and proposing solutions: a commentary.

Chenglin Ye¹, Lora Giangregorio, Anne Holbrook

¹Department of Mathematics and Statistics, McMaster University, Hamilton, Ontario, Canada; Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada; Biostatistics Unit, St Joseph's Healthcare Hamilton, Hamilton, Ontario, Canada.

Contemporary Clinical Trials

|February 9, 2011

Summary

This summary is machine-generated.

Participant data withdrawal from randomized controlled trials (RCTs) causes missing data and bias. This commentary offers strategies to minimize data withdrawal impact in RCTs.

More Related Videos

A Clinical Trial Assessing the Safety, Efficacy, and Delivery of Olive-Oil-Based Three-Chamber Bags for Parenteral Nutrition

A Clinical Trial Assessing the Safety, Efficacy, and Delivery of Olive-Oil-Based Three-Chamber Bags for Parenteral Nutrition

Published on: September 20, 2019

Using Continuous Data Tracking Technology to Study Exercise Adherence in Pulmonary Rehabilitation

Using Continuous Data Tracking Technology to Study Exercise Adherence in Pulmonary Rehabilitation

Published on: November 8, 2013

Related Experiment Videos

Last Updated: Jun 4, 2026

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

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

Published on: January 8, 2020

A Clinical Trial Assessing the Safety, Efficacy, and Delivery of Olive-Oil-Based Three-Chamber Bags for Parenteral Nutrition

A Clinical Trial Assessing the Safety, Efficacy, and Delivery of Olive-Oil-Based Three-Chamber Bags for Parenteral Nutrition

Published on: September 20, 2019

Using Continuous Data Tracking Technology to Study Exercise Adherence in Pulmonary Rehabilitation

Using Continuous Data Tracking Technology to Study Exercise Adherence in Pulmonary Rehabilitation

Published on: November 8, 2013

Area of Science:

Clinical Trials
Research Ethics
Data Management

Background:

Participant withdrawal in randomized controlled trials (RCTs) is common, leading to missing data and potential withdrawal bias.
Data withdrawal, where participants request removal of all their collected data, poses significant challenges for bias mitigation.
Existing literature and guidelines offer limited specific direction on managing data withdrawal in research.

Discussion:

Ethical considerations and methodological challenges associated with participant data withdrawal in RCTs require careful attention.
Strategies for minimizing data withdrawal include clear informed consent processes detailing data handling post-withdrawal.
Addressing missing data through statistical methods like imputation is crucial during the analysis phase.

Key Insights:

Lack of definitive guidelines for data withdrawal necessitates proactive strategies in RCTs.
Informed consent forms should explicitly outline data handling procedures following participant withdrawal.
Imputation techniques can effectively manage missing data resulting from data withdrawal.

Outlook:

Developing standardized protocols for data withdrawal is essential for maintaining RCT integrity.
Further research into participant motivations for data withdrawal can inform preventative measures.
Implementing proposed recommendations can enhance the robustness of RCT findings despite data withdrawal challenges.