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

Decision Making01:20

Decision Making

1.2K
Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
Automatic decision-making is fast, intuitive, and relies on gut feelings...
1.2K
Decision Making: Traditional Method01:14

Decision Making: Traditional Method

5.8K
The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
5.8K
Decision Making: P-value Method01:09

Decision Making: P-value Method

7.3K
The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim  is also stated. These statements can act as null and alternative hypotheses:  a null hypothesis would be a neutral statement while the alternative hypothesis can...
7.3K
Reason and Intuition01:37

Reason and Intuition

7.7K
The human brain processes information for decision-making using one of two routes: an intuitive system and a rational system (Epstein, 1994; popularized by Kahneman, 2011 as System 1 and System 2, respectively). The intuitive system is quick, impulsive, and operates with minimal effort, relying on emotions or habits to provide cues for what to do next, while the rational system is logical, analytical, deliberate, and methodical. Research in neuropsychology suggests that the...
7.7K
Causes of Similarity-Dissimilarity Effect01:26

Causes of Similarity-Dissimilarity Effect

344
The similarity-dissimilarity effect, a fundamental concept in social psychology, explains how interpersonal similarities and differences influence attraction and social interactions. This effect is supported by three key psychological perspectives: balance theory, social comparison theory, and consensual validation.Balance Theory and Cognitive ConsistencyBalance theory, developed by Fritz Heider, posits that individuals seek cognitive consistency in their relationships. When two people share...
344
Theory of Attribution II: Kelley's Covariation Theory01:29

Theory of Attribution II: Kelley's Covariation Theory

937
Attribution theory plays a crucial role in social psychology, helping to explain how individuals interpret the causes of behavior. One prominent model within this field is Harold Kelley's covariation theory, which provides a systematic approach to determining whether internal traits or external circumstances drive a person's actions. The model posits that individuals rely on three key types of information—consensus, consistency, and distinctiveness—to make these judgments.Consensus:...
937

You might also read

Related Articles

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

Sort by
Same author

The interplay between selective attention and summary statistics.

The Behavioral and brain sciences·2025
Same author

A selective sampling account of forming numerosity representations.

Psychological review·2025
Same author

Using diffusion models for symbolic numeracy tasks to examine aging effects.

Journal of experimental psychology. Learning, memory, and cognition·2024
Same author

Beyond discrete-choice options.

Trends in cognitive sciences·2024
Same author

Parsing memory and nonmemory contributions to age-related declines in mnemonic discrimination performance: a hierarchical Bayesian diffusion decision modeling approach.

Learning & memory (Cold Spring Harbor, N.Y.)·2023
Same author

Reexamining the effects of speed-accuracy instructions with a diffusion-model-based analysis.

Journal of experimental psychology. Learning, memory, and cognition·2023
Same journal

Dual-systems and Fuzzy-trace Theory Predictions of COVID-19 Risk Taking in Young Adults.

Decision (Washington, D.C.)·2025
Same journal

Correction to Mullet and Stewart (2016).

Decision (Washington, D.C.)·2025
Same journal

Cognitive Graphs: Representational Substrates for Planning.

Decision (Washington, D.C.)·2025
Same journal

Discounting Future Reward in an Uncertain World.

Decision (Washington, D.C.)·2025
Same journal

Hierarchies improve individual assessment of temporal discounting behavior.

Decision (Washington, D.C.)·2021
Same journal

Is Cognitive Impairment Related to Violations of Rationality? A Laboratory Alcohol Intoxication Study Testing Transitivity of Preference.

Decision (Washington, D.C.)·2021
See all related articles

Related Experiment Video

Updated: Apr 6, 2026

A Two-interval Forced-choice Task for Multisensory Comparisons
07:13

A Two-interval Forced-choice Task for Multisensory Comparisons

Published on: November 9, 2018

11.6K

Individual Differences and Fitting Methods for the Two-Choice Diffusion Model of Decision Making.

Roger Ratcliff1, Russ Childers1

  • 1The Ohio State University.

Decision (Washington, D.C.)
|August 4, 2015
PubMed
Summary
This summary is machine-generated.

This study evaluates diffusion model fitting methods to understand individual differences. It provides guidance on selecting appropriate methods for clinical, neuropsychological, and educational testing.

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

3.1K
Measuring Delay Discounting in Humans Using an Adjusting Amount Task
07:47

Measuring Delay Discounting in Humans Using an Adjusting Amount Task

Published on: January 9, 2016

16.1K

Related Experiment Videos

Last Updated: Apr 6, 2026

A Two-interval Forced-choice Task for Multisensory Comparisons
07:13

A Two-interval Forced-choice Task for Multisensory Comparisons

Published on: November 9, 2018

11.6K
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

3.1K
Measuring Delay Discounting in Humans Using an Adjusting Amount Task
07:47

Measuring Delay Discounting in Humans Using an Adjusting Amount Task

Published on: January 9, 2016

16.1K

Area of Science:

  • Cognitive Psychology
  • Computational Neuroscience
  • Psychometrics

Background:

  • The diffusion model is a valuable tool for understanding cognitive processes underlying decision-making.
  • Assessing individual differences using the diffusion model requires robust fitting methods.

Purpose of the Study:

  • To examine methods for fitting the diffusion model and their ability to capture individual differences.
  • To determine the sensitivity of the diffusion model in detecting group differences and individual deficits.

Main Methods:

  • Utilized data from two experiments to obtain diffusion model parameters.
  • Conducted simulation studies to assess parameter recovery, biases, and standard deviations across various fitting methods.
  • Compared a standard chi-square method with a hierarchical Bayesian method.

Main Results:

  • Investigated the consistency of diffusion model parameters across different numbers of observations.
  • Evaluated the ability of different fitting methods to recover individual differences and detect group disparities.
  • Identified biases and standard deviations in recovered parameters across various fitting approaches.

Conclusions:

  • The findings offer a starting point for selecting diffusion model fitting methods.
  • Provides insights into the strengths and weaknesses of diffusion model analyses for individual differences.
  • Informs the application of diffusion models in clinical, neuropsychological, and educational assessments.