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 Making: Traditional Method01:14

Decision Making: Traditional Method

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...
Decision Making: P-value Method01:09

Decision Making: P-value Method

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 have a...
Decision Making01:20

Decision Making

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...
Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
Mechanistic Models: Overview of Compartment Models01:21

Mechanistic Models: Overview of Compartment Models

Mechanistic models, a category encompassing both physiological and compartmental modeling, differ from empirical models' approaches to incorporating known factors about the systems being modeled. Empirical models describe data with minimal assumptions, while mechanistic models aim to provide a robust description of available data by specifying assumptions and integrating known factors about the system. Compartmental analysis is a key example of a mechanistic model in pharmacokinetics and...
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...

You might also read

Related Articles

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

Sort by
Same author

Loot box purchases are associated with problem gambling severity and harms beyond traditional gambling activities.

Addictive behaviors·2026
Same author

Effects of methamphetamine on signalled probability in rats using concurrent chains.

Psychopharmacology·2026
Same author

Environmental Associations of Body Disposal in New Zealand Homicides.

International journal of offender therapy and comparative criminology·2026
Same author

The long and winding road to treatment for problem gambling: from problem awareness to treatment helpfulness.

Addictive behaviors·2025
Same author

The Profiles of People who Do not Engage in Positive Play while Gambling.

Journal of gambling studies·2025
Same author

Predictors of Change in Cannabis Use Status from Pre- to Post-Recreational Cannabis Legalization in Canada: Evidence from a Two-Wave Longitudinal National Survey.

Cannabis (Albuquerque, N.M.)·2025
Same journal

The Genoeconomics of Impulsive Intertemporal Choice: A Critical Review.

Journal of the experimental analysis of behavior·2026
Same journal

Shaping the extinction burst: Increasing its probability and preventing its emergence across topographies.

Journal of the experimental analysis of behavior·2026
Same journal

Evaluating the combined effects of effort and probability on monetary discounting.

Journal of the experimental analysis of behavior·2026
Same journal

An improved translational approach to studying persistence-strengthening effects of differential reinforcement of alternative behavior.

Journal of the experimental analysis of behavior·2026
Same journal

Interactions between the effects of food and water motivating operations on concurrent food- and water-reinforced responding in mice.

Journal of the experimental analysis of behavior·2026
Same journal

Odor-visual and visual-visual matching to sample with dogs.

Journal of the experimental analysis of behavior·2026
See all related articles

Related Experiment Video

Updated: Jun 3, 2026

Three Laboratory Procedures for Assessing Different Manifestations of Impulsivity in Rats
09:12

Three Laboratory Procedures for Assessing Different Manifestations of Impulsivity in Rats

Published on: March 17, 2019

A decision model for steady-state choice in concurrent chains.

Darren R Christensen1, Randolph C Grace

  • 1University of Melbourne, Australia.

Journal of the Experimental Analysis of Behavior
|April 1, 2011
PubMed
Summary
This summary is machine-generated.

A new steady-state decision model for concurrent chains choice accurately explains acquisition data. This model matches or surpasses existing choice models in fit, parsimony, and parameter invariance.

Keywords:
acquisitionchoiceconcurrent chainsconditioned reinforcementcontextual choice modeldecision modelhyperbolic value-added modelkey peckpigeons

More Related Videos

Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents
07:05

Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents

Published on: September 10, 2018

Related Experiment Videos

Last Updated: Jun 3, 2026

Three Laboratory Procedures for Assessing Different Manifestations of Impulsivity in Rats
09:12

Three Laboratory Procedures for Assessing Different Manifestations of Impulsivity in Rats

Published on: March 17, 2019

Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents
07:05

Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents

Published on: September 10, 2018

Area of Science:

  • Behavioral psychology
  • Decision-making models

Background:

  • Grace and McLean (2006) proposed a decision model for concurrent chains choice.
  • The model was extended to include initial- and terminal-link duration effects (Christensen & Grace, 2008, 2009a, 2009b).

Purpose of the Study:

  • Derive a steady-state responding expression from the decision model.
  • Develop a choice model that accounts for archival data.

Main Methods:

  • Derived a steady-state expression from the existing decision model.
  • Compared the derived model's goodness of fit, parsimony, and parameter invariance against archival data.

Main Results:

  • The steady-state decision model provides an account of archival data.
  • The model's performance is equal or superior to the contextual choice model (Grace, 1994) and hyperbolic value-added model (Mazur, 2001).

Conclusions:

  • The steady-state decision model validates understanding acquisition phenomena.
  • This approach bridges acquisition phenomena to explaining choice at the molar level.