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

Factorial Design02:01

Factorial Design

13.6K
Factorial Analysis is an experimental design that applies Analysis of Variance (ANOVA) statistical procedures to examine a change in a dependent variable due to more than one independent variable, also known as factors. Changes in worker productivity can be reasoned, for example, to be influenced by salary and other conditions, such as skill level. One way to test this hypothesis is by categorizing salary into three levels (low, moderate, and high) and skills sets into two levels (entry level...
13.6K
Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs01:15

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

90
Body: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...
90
Two-Way ANOVA01:17

Two-Way ANOVA

3.2K
The two-way ANOVA is an extension of the one-way ANOVA. It is a statistical test performed on three or more samples categorized by two factors - a row factor and a column factor. Ronald Fischer mentioned it in 1925 in his book 'Statistical Methods for Researchers.'
The two-way ANOVA analysis initially begins by stating the null hypothesis that there is an interaction effect between the two factors of a dataset. This effect can be visualized using line segments formed by joining the...
3.2K
Crossover Experiments01:16

Crossover Experiments

4.4K
Crossover experiments, also called the repeated-measurements design, is a study design in which all experimental units are exposed to all treatments in different periods. Crossover experiments are generally used in psychology, the pharmaceutical industry, agriculture, and medicine.
Crossover designs are performed even with smaller sample sizes since the samples can act as their controls. These are better than simple randomized trials since patients are exposed to all the treatments.
4.4K
Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs01:20

Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs

125
Body: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...
125
One-Way ANOVA01:18

One-Way ANOVA

10.9K
One-way ANOVA analyzes more than three samples categorized by one factor. For example, it can compare the average mileage of sports bikes. Here, the data is categorized by one factor - the company. However, one-way ANOVA cannot be used to simultaneously compare the sample mean of three or more samples categorized by two factors. An example of two factors would be sports bikes from different companies driven in different terrains, such as a desert or snowy landscape. Here, two-way ANOVA is used...
10.9K

You might also read

Related Articles

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

Sort by
Same author

Validation of a Tool to Evaluate Nursing Students' Electronic Health Record Competency in Simulation.

Nursing education perspectives·2024
Same author

Evaluation of Simulation Outcomes.

Annual review of nursing research·2021
Same author

Questions Regarding Substitution of Simulation for Clinical.

Clinical simulation in nursing·2020
Same author

An innovative academic-practice partnership to enhance the development and training of military nurses.

Journal of professional nursing : official journal of the American Association of Colleges of Nursing·2019
Same author

Using Student-Produced Video to Validate Head-to-Toe Assessment Performance.

The Journal of nursing education·2018
Same author

Student QSEN Participation During an Adult Medical-Surgical Rotation.

Nursing education perspectives·2016
Same journal

Low Resource, High Impact: Just-In-Time Training Toolkit in Response to a Public Health Crisis.

Clinical simulation in nursing·2025
Same journal

Effectiveness of In-situ Simulation on Clinical Competence for Nurses: A Systematic Review.

Clinical simulation in nursing·2025
Same journal

Development and Evaluation of a Metric-based Clinical Simulation Procedure for Assessing Ostomy Care in Nursing Practice.

Clinical simulation in nursing·2024
Same journal

Development and Evaluation of a Wearable Simulator System.

Clinical simulation in nursing·2023
Same journal

Nursing Students Reported More Positive Emotions about Training during COVID-19 After Using a Virtual Simulation Paired with an In-person Simulation.

Clinical simulation in nursing·2023
Same journal

Nursing Students' Experience of Using HoloPatient During the Coronavirus Disease 2019 Pandemic: A Qualitative Descriptive Study.

Clinical simulation in nursing·2023
See all related articles

Related Experiment Video

Updated: Dec 6, 2025

Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study
20:24

Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study

Published on: January 31, 2014

17.0K

Two-by-Two Factorial Design.

Katie Haerling Adamson1, Susan Prion2

  • 1University of Washington Tacoma School of Nursing and Healthcare Leadership, Tacoma, WA.

Clinical Simulation in Nursing
|October 7, 2020
PubMed
Summary
This summary is machine-generated.

Factorial designs efficiently compare multiple independent variables in simulation research. This study provides resources for implementing a two-by-two factorial design.

Keywords:
ANOVAFactorial designMethodsSimulation

More Related Videos

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

5.0K
Quadruple-Checkerboard: A Modification of the Three-Dimensional Checkerboard for Studying Drug Combinations
11:15

Quadruple-Checkerboard: A Modification of the Three-Dimensional Checkerboard for Studying Drug Combinations

Published on: July 24, 2021

5.2K

Related Experiment Videos

Last Updated: Dec 6, 2025

Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study
20:24

Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study

Published on: January 31, 2014

17.0K
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

5.0K
Quadruple-Checkerboard: A Modification of the Three-Dimensional Checkerboard for Studying Drug Combinations
11:15

Quadruple-Checkerboard: A Modification of the Three-Dimensional Checkerboard for Studying Drug Combinations

Published on: July 24, 2021

5.2K

Area of Science:

  • Simulation research methodology
  • Statistical modeling in scientific inquiry

Background:

  • Comparing multiple independent variables is crucial in simulation research.
  • Factorial designs offer an efficient approach to investigate these comparisons.

Purpose of the Study:

  • To introduce and illustrate the application of factorial designs in simulation research.
  • To provide practical resources for implementing factorial designs, specifically a two-by-two design.

Main Methods:

  • Utilizing factorial designs to analyze the effects of multiple independent variables.
  • Demonstrating a two-by-two factorial design with a practical example.
  • Providing supplementary resources for implementation.

Main Results:

  • Factorial designs enable efficient comparison of multiple independent variables.
  • A two-by-two factorial design serves as a foundational example for simulation studies.

Conclusions:

  • Factorial designs are a valuable tool for enhancing simulation research efficiency.
  • The provided resources facilitate the adoption of factorial designs in practice.