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...

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...

Random Sampling Method

Random Sampling Method

Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest. Among the various sampling methods used by...

Group Design

Group Design

The most basic experimental design involves two groups: the experimental group and the control group. The two groups are designed to be the same except for one difference— experimental manipulation. The experimental group gets the experimental manipulation—that is, the treatment or variable being tested—and the control group does not. Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between the two are due to...

Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs

Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs

Bioequivalence experimental study designs play a pivotal role in testing the effectiveness of various treatments. Key among these are the repeated measures, cross-over, carry-over, and Latin square designs. In the repeated measures design, each subject receives all treatments, allowing for temporal comparisons. This type of design is useful in reducing variability but requires careful planning to avoid bias.The cross-over design, an economical method, involves sequential administration of...

Wald-Wolfowitz Runs Test I

Wald-Wolfowitz Runs Test I

The Wald-Wolfowitz test, also known as the runs test, is a nonparametric statistical test used to assess the randomness of a sequence of two different types of elements (e.g., positive/negative values, successes/failures). It examines whether the order of the elements in a sequence is random or if there is a pattern or trend present. This nonparametric test applies to any ordered data despite the population and sample data distribution, even if a higher sample size is available.
The test works...

You might also read

Related Articles

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

Sort by

Same author

Calls for Stricter Legislation and Fear in the European Immigrant Community: Reflections of the Public Charge Debate Ongoing in the United States Comment on "A Crisis of Humanitarianism: Refugees at the Gates of Europe".

International journal of health policy and management·2020

Same author

Wearable inertial sensors and pressure MAT detect risk factors associated with ACL graft failure that are not possible with traditional return to sport assessments.

BMJ open sport & exercise medicine·2019

Same author

Local therapy for triple-negative breast cancer: a comprehensive review.

Future oncology (London, England)·2017

Same author

Self-rated health, objective health, and racial discrimination among African-Americans: Explaining inconsistent findings and testing health pessimism.

Journal of health psychology·2015

Same author

The effect of general anesthesia versus intravenous sedation on diagnostic yield and success in electromagnetic navigation bronchoscopy.

Journal of bronchology & interventional pulmonology·2015

Same author

Predicting Heart Failure Readmissions.

The Journal of cardiovascular nursing·2014

Search research articles

Related Experiment Video

Updated: Jun 4, 2026

Barnes Maze Testing Strategies with Small and Large Rodent Models

Barnes Maze Testing Strategies with Small and Large Rodent Models

Published on: February 26, 2014

Blocked randomization with randomly selected block sizes.

¹Center for Health Disparities Research and the Department of Public Health, Brody School of Medicine, East Carolina University, Physicians Quadrangle, Greenville, NC 27858, USA. jimmy.efird@stanfordalumni.org

International Journal of Environmental Research and Public Health

|February 15, 2011

Summary

Block randomization balances participants in clinical trials, preventing bias. Using random block sizes enhances allocation concealment, ensuring more reliable study results and avoiding predictable assignment patterns.

Keywords:

blocked randomization random block sizes randomized clinical trial

Related Experiment Videos

Last Updated: Jun 4, 2026

Barnes Maze Testing Strategies with Small and Large Rodent Models

Barnes Maze Testing Strategies with Small and Large Rodent Models

Published on: February 26, 2014

Area of Science:

Clinical Trials
Biostatistics
Medical Research Methodology

Background:

Randomized clinical trials require careful participant allocation to avoid selection and accidental bias.
Simple random allocation may lead to unequal group sizes, reducing statistical power.
Block randomization is a common method to ensure balance, especially in small trials.

Purpose of the Study:

To provide an overview of block randomization in clinical trial design.
To illustrate methods for avoiding selection bias through random block sizes.
To enhance the reliability of participant allocation in clinical studies.

Main Methods:

Review of block randomization principles in clinical trial design.
Explanation of how fixed block sizes can lead to predictable allocation.
Introduction of random block sizes to improve allocation concealment.

Main Results:

Block randomization effectively balances participant numbers across study arms.
Predictability in allocation can occur with fixed block sizes, compromising blinding.
Randomizing block sizes significantly reduces the risk of selection bias.

Conclusions:

Random block sizes are crucial for robust allocation concealment in clinical trials.
Implementing variable block sizes enhances the integrity of randomized study designs.
This approach strengthens the validity of findings from randomized controlled trials.