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

Chi-square Analysis02:46

Chi-square Analysis

44.7K
The chi-square test is a statistical hypothesis test. It is used to check whether there is a significant difference between an expected value and an observed value. In the context of genetics, it enables us to either accept or reject a hypothesis, based on how much the observed values deviate from the expected values.
The chi-square test was developed by Pearson in 1990.
The first step of performing a Chi-square analysis is to establish a null hypothesis, which assumes that there is no real...
44.7K
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

376
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...
376
Trihybrid Crosses02:27

Trihybrid Crosses

26.5K
Trihybrid Crosses
Some of Mendel’s crosses examined three pairs of contrasting characteristics. Such a cross is called a trihybrid cross. A trihybrid cross is a combination of three individual monohybrid crosses. For example, plant height (tall vs. short), seed shape (round vs. wrinkled), and seed color (yellow vs. green).
The F1 generation plants of a trihybrid cross are heterozygous for all three traits and produce eight gametes. Upon self-fertilization, these gametes have an equal...
26.5K
Punnett Squares01:00

Punnett Squares

127.4K
Overview
127.4K
Punnett Squares01:00

Punnett Squares

15.2K
15.2K
Crossover Experiments01:16

Crossover Experiments

4.7K
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.
4.7K

You might also read

Related Articles

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

Sort by
Same author

A note on point estimation and interval estimation of the relative treatment effect under a simple crossover design.

Pharmaceutical statistics·2021
Same author

Urinary metabolites of furan in waterpipe tobacco smokers compared to non-smokers in home settings in the US.

Toxicology letters·2020
Same author

Exact Confidence Limits on Some New Measures of Concordance and Discordance in Binary Outcomes.

Therapeutic innovation & regulatory science·2020
Same author

Exact interval estimators for some commonly used measures of binary agreement.

Statistics in medicine·2019
Same author

Asymptotic and exact interval estimators of the common odds ratio under the sequential parallel comparison design.

Statistical methods in medical research·2018
Same author

Exact and asymptotic tests under the sequential parallel comparison design.

Pharmaceutical statistics·2018

Related Experiment Video

Updated: Mar 22, 2026

Frequency and Distribution of Crossovers in Caenorhabditis elegans Meiosis by SNP Genotyping using Real-time PCR
06:18

Frequency and Distribution of Crossovers in Caenorhabditis elegans Meiosis by SNP Genotyping using Real-time PCR

Published on: July 11, 2025

1.0K

Test equality in binary data for a 4 × 4 crossover trial under a Latin-square design.

Kung-Jong Lui1, Kuang-Chao Chang2

  • 1Department of Mathematics and Statistics, College of Sciences, San Diego State University, San Diego, CA, 92182-7720, U.S.A.

Statistics in Medicine
|April 23, 2016
PubMed
Summary

This study introduces a 4x4 Latin square design for crossover trials with binary data, simplifying comparisons between experimental and control treatments. New statistical methods offer accurate testing and interval estimation for treatment effects.

Keywords:
Latin squareType I errorbinary datacarry-over effectcoverage probabilitycrossover trialrandom effects

More Related Videos

Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects
08:13

Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects

Published on: May 10, 2019

6.9K
Assessing Differences in Sperm Competitive Ability in Drosophila
09:34

Assessing Differences in Sperm Competitive Ability in Drosophila

Published on: August 22, 2013

15.1K

Related Experiment Videos

Last Updated: Mar 22, 2026

Frequency and Distribution of Crossovers in Caenorhabditis elegans Meiosis by SNP Genotyping using Real-time PCR
06:18

Frequency and Distribution of Crossovers in Caenorhabditis elegans Meiosis by SNP Genotyping using Real-time PCR

Published on: July 11, 2025

1.0K
Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects
08:13

Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects

Published on: May 10, 2019

6.9K
Assessing Differences in Sperm Competitive Ability in Drosophila
09:34

Assessing Differences in Sperm Competitive Ability in Drosophila

Published on: August 22, 2013

15.1K

Area of Science:

  • Biostatistics
  • Clinical Trial Design

Background:

  • Crossover designs are valuable for clinical trials but become complex with many treatments.
  • Complete treatment sequences in binary crossover trials are impractical for four or more treatments.

Purpose of the Study:

  • To develop statistical procedures for comparing experimental treatments against a control in a 4x4 Latin square crossover trial.
  • To provide closed-form interval estimators for relative treatment effects in dichotomous outcome crossover trials.
  • To assess the performance of proposed methods using Monte Carlo simulations.

Main Methods:

  • Utilized a 4x4 Latin square design to reduce treatment sequences.
  • Developed a distribution-free random effects logistic regression model.
  • Derived simple procedures for hypothesis testing and interval estimation.

Main Results:

  • The proposed methods are effective for testing non-equality between experimental and control treatments.
  • Closed-form interval estimators for relative effects were successfully derived.
  • Monte Carlo simulations demonstrated the performance of the developed procedures.

Conclusions:

  • The 4x4 Latin square design and associated statistical methods offer a practical approach for analyzing dichotomous data in crossover trials with multiple treatments.
  • The developed procedures and estimators are valuable tools for clinical trial analysis.