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

Contingency Table01:29

Contingency Table

A contingency table provides a way of portraying data that can facilitate calculating probabilities. It is a method of displaying a frequency distribution as a table with rows and columns to show how two variables may be dependent (contingent) upon each other; The table helps determine conditional probabilities quite quickly and can help systematically organize, analyze and quantify data. The table displays sample values concerning two variables that may be dependent or contingent on one...
Naturalistic Observations02:30

Naturalistic Observations

If you want to understand how behavior occurs, one of the best ways to gain information is to simply observe the behavior in its natural context. However, people might change their behavior in unexpected ways if they know they are being observed. How do researchers obtain accurate information when people tend to hide their natural behavior? As an example, imagine that your professor asks everyone in your class to raise their hand if they always wash their hands after using the restroom. Chances...
Determination of Expected Frequency01:08

Determination of Expected Frequency

Suppose one wants to test independence between the two variables of a contingency table. The values in the table constitute the observed frequencies of the dataset. But how does one determine the expected frequency of the dataset? One of the important assumptions is that the two variables are independent, which means the variables do not influence each other. For independent variables, the statistical probability of any event involving both variables is calculated by multiplying the individual...
Introduction to Test of Independence01:21

Introduction to Test of Independence

In statistics, the term independence means that one can directly obtain the probability of any event involving both variables by multiplying their individual probabilities. Tests of independence are chi-square tests involving the use of a contingency table of observed (data) values.
The test statistic for a test of independence is similar to that of a goodness-of-fit test:
Observational Studies01:11

Observational Studies

Observational studies are a type of analytical study where researchers observe events without any interventions. In other words, the researcher does not influence the response variable or the experiment's outcome.
There are three types of observational studies – Prospective, retrospective, and cross-sectional.
Prospective Study
Prospective studies, also known as longitudinal or cohort studies, are carried out by collecting future data from groups sharing similar characteristics. One example of...
Hypothesis Test for Test of Independence01:16

Hypothesis Test for Test of Independence

The test of independence is a chi-square-based test used to determine whether two variables or factors are independent or dependent. This hypothesis test is used to examine the independence of the variables. One can construct two qualitative survey questions or experiments based on the variables in a contingency table. The goal is to see if the two variables are unrelated (independent) or related (dependent). The null and alternative hypotheses for this test are:
H0: The two variables (factors)...

You might also read

Related Articles

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

Sort by
Same author

Twenty-five years of simulated demand: A bibliometric and systematic review of hypothetical drug purchase tasks.

Journal of the experimental analysis of behavior·2026
Same author

Risk identification strategies for health pandemics and epidemics on college campuses: A comprehensive analysis of heat maps and behavioral observations.

PloS one·2026
Same author

The Effect of Price on the Behavioural Economic Substitutability of Non-Alcoholic and Alcoholic Beverages.

Drug and alcohol review·2026
Same author

Preclinical abuse potential testing using behavioral economics and drug self-administration demand-curve analysis: A strategy to improve resolution of drug stratification for regulatory control.

Pharmacological reviews·2026
Same author

An Analysis of Variables Contributing to Board Certified Behavior Analyst<sup>®</sup> Turnover.

Behavior analysis in practice·2026
Same author

Evaluating contributions of progressive ratio analysis to economic metrics of demand.

Journal of the experimental analysis of behavior·2025
Same journal

Latency and persistence of renewal in an intensive outpatient clinic.

Journal of applied behavior analysis·2026
Same journal

The effect of varied versus constant high-probability instructional sequences on cooperation.

Journal of applied behavior analysis·2026
Same journal

Relations between heart rate and precursors: A replication and extension of prior research.

Journal of applied behavior analysis·2026
Same journal

Integrating five linear trend techniques into performance-criteria-based effect size measurements: Impressions and recommendations.

Journal of applied behavior analysis·2026
Same journal

Functional analysis and treatment of higher level restricted repetitive behavior displayed by individuals with autism.

Journal of applied behavior analysis·2026
Same journal

Contingency drives children's vocal behavior.

Journal of applied behavior analysis·2026
See all related articles

Related Experiment Video

Updated: Jul 5, 2026

RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans
11:09

RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans

Published on: July 17, 2021

Contingency space analysis: an alternative method for identifying contingent relations from observational data.

Brian K Martens1, Florence D Digennaro, Derek D Reed

  • 1Department of Psychology, Syracuse University, 430 Huntington Hall, Syracuse, New York 13244, USA.

Journal of Applied Behavior Analysis
|May 13, 2008
PubMed
Summary
This summary is machine-generated.

This study introduces contingency space analysis (CSA) to improve descriptive assessments of behavior-consequence relations. CSA offers a novel strategy for designing effective behavior intervention programs.

More Related Videos

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
13:00

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Published on: January 23, 2017

Related Experiment Videos

Last Updated: Jul 5, 2026

RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans
11:09

RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans

Published on: July 17, 2021

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
13:00

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Published on: January 23, 2017

Area of Science:

  • Behavior Analysis
  • Applied Behavior Analysis
  • Psychology

Background:

  • Descriptive assessment methods are crucial for identifying problem behavior consequences.
  • Current methods lack consensus on optimal data and analytic strategies for behavior-consequence relations.
  • Sequential recording and conditional probability analysis show promise.

Purpose of the Study:

  • To review strategies for identifying contingent relations from conditional probabilities.
  • To propose and detail a novel method: contingency space analysis (CSA).
  • To discuss CSA's utility in descriptive assessment, intervention design, and treatment evaluation.

Main Methods:

  • Review of existing strategies for analyzing conditional probabilities.
  • Introduction and step-by-step procedural explanation of contingency space analysis (CSA).
  • Demonstration of CSA using sample data.

Main Results:

  • Conditional probability analysis is a useful tool for behavior-consequence relations.
  • Contingency space analysis (CSA) provides a structured approach to this analysis.
  • Sample data interpretation illustrates CSA's application.

Conclusions:

  • Contingency space analysis (CSA) offers a valuable tool for descriptive assessments.
  • CSA can inform the design of effective behavior intervention strategies.
  • CSA aids in evaluating changes in reinforcement contingencies post-treatment.