Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Self-Report Tests of Personality

Self-Report Tests of Personality

Self-report inventories are objective personality assessments that use multiple-choice items or numbered scales, typically ranging from 1 (strongly disagree) to 5 (strongly agree). They are often called Likert scales after Rensis Likert. These inventories are widely used due to their ease of administration and cost-effectiveness. One of the most prominent examples is the Minnesota Multiphasic Personality Inventory (MMPI), initially developed in the 1940s to assess abnormal personality traits.

Diagnostic and Statistical Manual of Mental Disorders (DSM)

Diagnostic and Statistical Manual of Mental Disorders (DSM)

The Diagnostic and Statistical Manual of Mental Disorders (DSM) serves as the primary classification system for mental health disorders, providing standardized diagnostic criteria for clinicians and researchers. First published by the American Psychiatric Association (APA) in 1952, the DSM has undergone several revisions to reflect evolving psychiatric understanding. The fifth edition, DSM-5, released in 2013, introduced key updates that expanded diagnostic categories and modified diagnostic...

Multiple Comparison Tests

Multiple Comparison Tests

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...

You might also read

Related Articles

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

Sort by

Same author

Understanding Rater Cognition in Performance Assessment: A Mixed IRTree Approach.

Applied psychological measurement·2025

Same author

Exploring the Influence of Response Styles on Continuous Scale Assessments: Insights From a Novel Modeling Approach.

Educational and psychological measurement·2024

Same author

Modeling Rating Order Effects Under Item Response Theory Models for Rater-Mediated Assessments.

Applied psychological measurement·2023

Same author

A Mixture IRTree Model for Performance Decline and Nonignorable Missing Data.

Educational and psychological measurement·2020

Same author

Utilizing response times in cognitive diagnostic computerized adaptive testing under the higher-order deterministic input, noisy 'and' gate model.

The British journal of mathematical and statistical psychology·2019

Same journal

A Kurtosis-Adjusted Bias Correction for the Standardized Mean Difference: Extending Hedges' <i>g</i> to Nonnormal Populations.

Educational and psychological measurement·2026

Same journal

A Simple Approach for Differential Test Functioning Based on Sum Scores.

Educational and psychological measurement·2026

Same journal

Evaluating Factor Retention in Large Factor Analysis Models: A Simulation Study Comparing 15 Methods.

Educational and psychological measurement·2026

Same journal

Agreement and Alignment in Binary Rating Tasks: Strategic Convergence as an Equilibrium Outcome.

Educational and psychological measurement·2026

Same journal

Interactions Between Termination Criteria and Ability Estimators in Computerized Adaptive Testing.

Educational and psychological measurement·2026

Same journal

Identification and Diagnosis of Misreporting in Surveys.

Educational and psychological measurement·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Aug 15, 2025

Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education

Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education

Published on: August 16, 2024

Diagnostic Classification Model for Forced-Choice Items and Noncognitive Tests.

Hung-Yu Huang¹

¹University of Taipei, Taiwan.

Educational and Psychological Measurement

|January 5, 2023

Summary

This summary is machine-generated.

This study introduces a new Diagnostic Classification Model (DCM) for forced-choice (FC) items to simultaneously manage response biases and classify latent traits. The model shows promising parameter recovery with sufficient data, offering advancements for noncognitive testing.

Keywords:

Bayesian estimation diagnostic classification model forced-choice format pairwise comparison

More Related Videos

Computerized Adaptive Testing System of Functional Assessment of Stroke

Computerized Adaptive Testing System of Functional Assessment of Stroke

Published on: January 7, 2019

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

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

Published on: January 11, 2020

Related Experiment Videos

Last Updated: Aug 15, 2025

Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education

Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education

Published on: August 16, 2024

Computerized Adaptive Testing System of Functional Assessment of Stroke

Computerized Adaptive Testing System of Functional Assessment of Stroke

Published on: January 7, 2019

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

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

Published on: January 11, 2020

Area of Science:

Psychometrics
Educational Measurement
Psychological Assessment

Background:

Forced-choice (FC) item formats are common in noncognitive tests to mitigate response biases.
Diagnostic Classification Models (DCMs) are widely used for cognitive tests but less so for noncognitive ones.
Existing DCMs often do not simultaneously address response biases and provide diagnostic classifications for FC items.

Purpose of the Study:

To develop a novel class of DCMs within a higher-order framework specifically for FC items.
To enable simultaneous control of response biases and diagnostic classification of latent traits.
To address practical demands in noncognitive assessment.

Main Methods:

Development of a new higher-order DCM for FC items.
Extensive simulations to evaluate model performance.
Bayesian estimation for model parameter calibration.
Empirical analysis using work-motivation measures.

Main Results:

The proposed DCM demonstrates satisfactory parameter recovery with long tests and large sample sizes.
Increased number of attributes enhances second-order latent trait estimation precision but can reduce classification accuracy.
Specific-attribute loading in paired comparison items yields superior parameter estimation compared to overlap-attribute conditions.

Conclusions:

The new DCM effectively integrates response bias control with diagnostic classification for FC items.
The model offers a valuable tool for advancing noncognitive assessment in educational and psychological settings.
Findings support the utility of the model in real-world applications, as shown by the work-motivation analysis.