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

Case Studies01:22

Case Studies

13.2K
There are many research methods available to psychologists in their efforts to understand, describe, and explain behavior and the cognitive and biological processes that underlie it.
13.2K
Multiple Comparison Tests01:13

Multiple Comparison Tests

4.3K
Multiple comparison test, abbreviated as MCT, is a post hoc analysis generally performed after comparing multiple samples with one or more tests. An MCT will help identify a significantly different sample among multiple samples or a factor among multiple factors.
It would be easy to compare two samples using a significance alpha level of 0.05. In other words, there is only one sample pair to be compared. However, it would be difficult to identify a significantly different sample if the number...
4.3K
Sign Test for Matched Pairs01:17

Sign Test for Matched Pairs

339
The sign test for matched pairs offers a robust method for comparing two paired samples, often for the effects of an intervention in one of them. This method is very useful in situations where the underlying distribution of the data is unknown. The test compares two related samples—often pre- and post-treatment measurements on the same subjects—to determine if there are significant differences in their median values.
To conduct the sign test, we first calculate the differences in...
339
Testing a Claim about Population Proportion01:24

Testing a Claim about Population Proportion

3.8K
A complete procedure for testing a claim about a population proportion is provided here.
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...
3.8K
Statistical Analysis: Overview01:11

Statistical Analysis: Overview

13.7K
When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
13.7K
Statistical Hypothesis Testing01:16

Statistical Hypothesis Testing

5.6K
Hypothesis testing is a critical statistical procedure facilitating informed, evidence-based decisions. It begins with a hypothesis, which is a tentative explanation, or a prediction about a population parameter. This hypothesis can be either a null hypothesis (H0), indicating no effect or difference, or an alternative hypothesis (Ha), suggesting an effect or difference.
Statistical significance measures the probability that an observed result occurred by chance. If this probability, known as...
5.6K

You might also read

Related Articles

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

Sort by
Same author

Machine Learning to Detect Vocal Stereotypy: Improving Duration-Based Measures.

Behavior modification·2025
Same author

Machine learning to detect schedules using spatiotemporal data of behavior: A proof of concept.

Journal of the experimental analysis of behavior·2025
Same author

The Family Game to support parents with intellectual disability in managing challenging behaviours: A replication.

Journal of applied research in intellectual disabilities : JARID·2024
Same author

Brief Report: Virtual Reality to Raise Awareness About Autism.

Journal of autism and developmental disorders·2023
Same author

Tutorial: Artificial neural networks to analyze single-case experimental designs.

Psychological methods·2022
Same author

Agreement between visual inspection and objective analysis methods: A replication and extension.

Journal of applied behavior analysis·2022

Related Experiment Video

Updated: Dec 20, 2025

Cross-Modal Multivariate Pattern Analysis
13:51

Cross-Modal Multivariate Pattern Analysis

Published on: November 9, 2011

20.3K

Machine Learning to Analyze Single-Case Data: A Proof of Concept.

Marc J Lanovaz1, Antonia R Giannakakos2, Océane Destras3

  • 11École de Psychoéducation, Université de Montréal, C.P. 6128, succursale Centre-Ville, Montreal, QC H3C 3J7 Canada.

Perspectives on Behavior Science
|May 23, 2020
PubMed
Summary

Machine learning algorithms enhance the interpretation of single-case design data, outperforming traditional visual analysis methods. These algorithms offer improved accuracy and statistical power for behavior analysts.

Keywords:
AB designArtificial intelligenceError rateMachine learningSingle-case design

More Related Videos

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

7.8K
Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
09:20

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

9.1K

Related Experiment Videos

Last Updated: Dec 20, 2025

Cross-Modal Multivariate Pattern Analysis
13:51

Cross-Modal Multivariate Pattern Analysis

Published on: November 9, 2011

20.3K
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

7.8K
Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
09:20

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

9.1K

Area of Science:

  • Behavior Analysis
  • Data Science
  • Research Methodology

Background:

  • Visual analysis is standard for single-case designs but faces interrater agreement challenges.
  • Structured aids like the dual-criteria (DC) method improve agreement but may lack optimal accuracy.

Purpose of the Study:

  • To assess the alignment between visual analysis and machine learning (ML) models.
  • To compare the performance (accuracy, Type I error, power) of ML models against the DC method.

Main Methods:

  • ML models were trained on existing single-case design data.
  • Analyses were conducted on both real and simulated datasets.
  • Performance metrics were compared between ML models and the DC method.

Main Results:

  • ML models demonstrated higher agreement with visual analysis interpretations than the DC method.
  • ML algorithms surpassed the DC method in accuracy, Type I error rate, and statistical power.

Conclusions:

  • ML algorithms show promise for supplementing visual analysis in single-case designs.
  • Further research is required to fully understand the implications of using ML in behavior analysis.