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

Response Surface Methodology01:16

Response Surface Methodology

750
Response Surface Methodology (RSM) is a collection of statistical and mathematical techniques used to develop, improve, and optimize processes. It is particularly valuable when many input variables or factors potentially influence a response variable.
The process of RSM involves several key steps:
750
Noncompartmental Analysis: Mean Residence Time01:05

Noncompartmental Analysis: Mean Residence Time

680
According to statistical moment theory, mean residence time (MRT) is an important measure in pharmacokinetics. MRT can be defined as the expected mean of a probability density function distribution. It provides valuable insights into drug disposition in the body.
After the administration of a drug through intravenous bolus injection, the drug molecules are distributed throughout the body and remain there for varying periods. The MRT represents the average time these drug molecules stay in the...
680

You might also read

Related Articles

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

Sort by
Same author

Disentangling individual differences in cognitive response mechanisms for rating scale items: A flexible-mixture multidimensional IRTree approach.

Behavior research methods·2025
Same author

Disentangling Qualitatively Different Faking Strategies in High-Stakes Personality Assessments: A Mixture Extension of the Multidimensional Nominal Response Model.

Educational and psychological measurement·2025
Same author

Item Response Models for Rating Relational Data.

Psychometrika·2025
Same author

"What If Applicants Fake Their Responses?": Modeling Faking and Response Styles in High-Stakes Assessments Using the Multidimensional Nominal Response Model.

Educational and psychological measurement·2025
Same author

Investigating heterogeneity in IRTree models for multiple response processes with score-based partitioning.

The British journal of mathematical and statistical psychology·2024
Same author

Investigating Heterogeneity in Response Strategies: A Mixture Multidimensional IRTree Approach.

Educational and psychological measurement·2024
Same journal

Proficiency order invariance of MLE, MAP, EAP, and WLE in item response theory.

The British journal of mathematical and statistical psychology·2026
Same journal

Bias and precision in true-score estimation.

The British journal of mathematical and statistical psychology·2026
Same journal

Polychoric correlations under the assumption of elliptical latent traits.

The British journal of mathematical and statistical psychology·2026
Same journal

Regularized reduced rank regression for mixed predictor and response variables.

The British journal of mathematical and statistical psychology·2026
Same journal

A multiple-choice SDT model for cognitive diagnosis models.

The British journal of mathematical and statistical psychology·2026
Same journal

Modular item response and structural equation modelling via measurement and uncertainty preserving parametric modelling.

The British journal of mathematical and statistical psychology·2026
See all related articles

Related Experiment Video

Updated: Mar 8, 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

10.3K

Response style analysis with threshold and multi-process IRT models: A review and tutorial.

Ulf Böckenholt1, Thorsten Meiser2

  • 1Northwestern University, Evanston, Illinois, USA.

The British Journal of Mathematical and Statistical Psychology
|January 29, 2017
PubMed
Summary
This summary is machine-generated.

Two item response theory (IRT) frameworks assess response styles in rating data. Both models account for response styles but differ in model selection, estimation, and conceptualization of individual differences.

Keywords:
MPLUSattitudinal measurementitem-response tree modelsresponse stylethreshold item-response models

More Related Videos

An Emerging Target Paradigm to Evoke Fast Visuomotor Responses on Human Upper Limb Muscles
09:27

An Emerging Target Paradigm to Evoke Fast Visuomotor Responses on Human Upper Limb Muscles

Published on: August 25, 2020

4.8K
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

Related Experiment Videos

Last Updated: Mar 8, 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

10.3K
An Emerging Target Paradigm to Evoke Fast Visuomotor Responses on Human Upper Limb Muscles
09:27

An Emerging Target Paradigm to Evoke Fast Visuomotor Responses on Human Upper Limb Muscles

Published on: August 25, 2020

4.8K
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

Area of Science:

  • Psychometrics
  • Psychological Assessment
  • Statistical Modeling

Background:

  • Response styles can bias rating data.
  • Existing item response theory (IRT) models offer frameworks for their assessment.
  • Two distinct IRT frameworks exist for analyzing response styles.

Purpose of the Study:

  • To review and compare two IRT frameworks for assessing response styles.
  • To illustrate these frameworks using empirical data on the 'Personal Need for Structure' construct.
  • To evaluate the frameworks based on quantitative, practical, and conceptual criteria.

Main Methods:

  • Analysis of threshold parameters in Rasch models and mixture-distribution extensions.
  • Application of multi-process item response tree models.
  • Utilizing Mplus software for model estimation and comparison.

Main Results:

  • Both IRT frameworks effectively account for response styles in rating data.
  • Significant differences were observed in model selection criteria and estimation.
  • Conceptual distinctions emerged regarding the representation of response styles.

Conclusions:

  • The choice between frameworks depends on specific research goals and data characteristics.
  • Both approaches offer valuable insights into response styles, but differ in their representation of individual differences.
  • Further research is needed to refine the conceptualization and application of these models in psychological assessment.