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

Randomized Experiments01:13

Randomized Experiments

6.8K
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...
6.8K
Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

164
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
164
Statistical Methods to Analyze Parametric Data: ANOVA01:12

Statistical Methods to Analyze Parametric Data: ANOVA

302
Analysis of Variance, or ANOVA, is a powerful statistical technique used to analyze parametric data, primarily in research and experimental studies. It's designed to compare the means of two or more groups, assisting researchers in identifying any significant differences between these group means. There are two main types of ANOVA based on the complexity of the analysis: one-way and two-way.
One-way ANOVA is applied when a single independent variable or factor is scrutinized. It compares...
302
Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data01:16

Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data

117
Statistical inference techniques, paramount in hypothesis testing, differentiate into two broad categories: parametric and nonparametric statistics.
Parametric statistics, as the name suggests, assumes that data follow a specific distribution, often a normal distribution. This assumption enables robust hypothesis testing and estimation. Parametric methods, like the Student's t-test or Goodness-of-fit test, are frequently employed in biostatistics due to their robustness. For instance,...
117
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

124
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,...
124
Hazard Ratio01:12

Hazard Ratio

103
The hazard ratio (HR) is a widely used measure in clinical trials to compare the risk of events, such as death or disease recurrence, between two groups over time. It reflects the ratio of hazard rates—the instantaneous risk of the event occurring—between a treatment group and a control group. This measure provides valuable insights into the relative effectiveness of a treatment by assessing how the risk of an event differs between the two groups.
For example, in a clinical trial...
103

You might also read

Related Articles

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

Sort by
Same author

Robust Metabolomics Data Normalization across Scales and Experimental Designs.

Analytical chemistry·2026
Same author

The Future Toolbox for Managing Ketosis in Dairy Cow Herds: A European Key Opinion Leader Consensus.

Veterinary sciences·2026
Same author

Challenges and Good Practices in Preprocessing and Normalization of Untargeted DNA Adductomics Data in Exposomics Research.

Analytical chemistry·2026
Same author

Standardized digital PCR assay validation using PCR-ValiPal, demonstrated in cross-platform quantification of bovine papilloma virus.

Analytica chimica acta·2026
Same author

Validation and clinical study of single-step vitrification combined with single-step warming of human blastocysts.

Journal of assisted reproduction and genetics·2026
Same author

A repository of the salivary metabolome and its key drivers in 1436 European children.

EBioMedicine·2025

Related Experiment Video

Updated: Jun 16, 2025

Strategies for Assessing Autistic-Like Behaviors in Mice
07:38

Strategies for Assessing Autistic-Like Behaviors in Mice

Published on: September 20, 2024

917

Treatment randomisation at animal or pen level? : Statistical analysis should follow the randomisation pattern!

Luc Duchateau1, Robrecht Dockx2, Klara Goethals1

  • 1Biometrics Research Centre, Faculty of Veterinary Medicine, Ghent University, Belgium.

Laboratory Animals
|August 19, 2024
PubMed
Summary

Random treatment assignment is crucial for establishing causality in research. Proper randomization ensures groups are comparable, allowing valid statistical analysis and reliable outcome interpretation.

Keywords:
Mycoplasma hyopneumoniaeRandomisationclustered-randomised trialsrepeated measurementsreplication

More Related Videos

An Automated T-maze Based Apparatus and Protocol for Analyzing Delay- and Effort-based Decision Making in Free Moving Rodents
07:42

An Automated T-maze Based Apparatus and Protocol for Analyzing Delay- and Effort-based Decision Making in Free Moving Rodents

Published on: August 2, 2018

13.6K
A Within-Subject Experimental Design using an Object Location Task in Rats
09:28

A Within-Subject Experimental Design using an Object Location Task in Rats

Published on: May 6, 2021

4.5K

Related Experiment Videos

Last Updated: Jun 16, 2025

Strategies for Assessing Autistic-Like Behaviors in Mice
07:38

Strategies for Assessing Autistic-Like Behaviors in Mice

Published on: September 20, 2024

917
An Automated T-maze Based Apparatus and Protocol for Analyzing Delay- and Effort-based Decision Making in Free Moving Rodents
07:42

An Automated T-maze Based Apparatus and Protocol for Analyzing Delay- and Effort-based Decision Making in Free Moving Rodents

Published on: August 2, 2018

13.6K
A Within-Subject Experimental Design using an Object Location Task in Rats
09:28

A Within-Subject Experimental Design using an Object Location Task in Rats

Published on: May 6, 2021

4.5K

Area of Science:

  • Experimental design
  • Biostatistics
  • Animal research methodology

Background:

  • Establishing a causal link between treatments and outcomes requires rigorous study design.
  • Random treatment assignment is a cornerstone of unbiased experimental research.
  • Ensuring comparability between treatment groups is vital for valid conclusions.

Purpose of the Study:

  • To emphasize the critical role of random treatment assignment in causal inference.
  • To highlight how randomization minimizes systematic bias in experimental studies.
  • To underscore the importance of aligning statistical analysis with the randomization pattern.

Main Methods:

  • Utilizing random allocation to assign subjects to different experimental groups.
  • Implementing robust randomization techniques to ensure unpredictability.
  • Documenting the randomization process meticulously.

Main Results:

  • Randomization effectively prevents systematic differences between treatment groups, other than the intervention itself.
  • It ensures that observed effects are attributable to the treatment, not pre-existing variations.
  • The integrity of the randomization process directly impacts the validity of the results.

Conclusions:

  • Random treatment assignment is indispensable for demonstrating causality.
  • Adherence to randomization principles enhances the reliability and interpretability of research findings.
  • The randomization strategy must inform the subsequent statistical analysis plan.