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

Classification of Illness01:17

Classification of Illness

8.0K
The meaning of illness is individualized to each person who experiences an alteration in health. In contrast, disease is a medical term indicating a pathological change in the structure and function of the body or mind. It is a condition that has specific symptoms and boundaries.
An illness is a response to a disease in which the person's level of functioning is changed compared with a previous level. The general classification of illness includes acute and chronic.
Acute illness is severe...
8.0K
Receiver Operating Characteristic Plot01:15

Receiver Operating Characteristic Plot

342
A ROC (Receiver Operating Characteristic) plot is a graphical tool used to assess the performance of a binary classification model by illustrating the trade-off between sensitivity (true positive rate) and specificity (false positive rate). By plotting sensitivity against 1 - specificity across various threshold settings, the ROC curve shows how well the model distinguishes between classes, with a curve closer to the top-left corner indicating a more accurate model. The area under the ROC curve...
342
Sensitivity, Specificity, and Predicted Value01:13

Sensitivity, Specificity, and Predicted Value

699
In healthcare diagnostics, laboratory tests play a crucial role in identifying and diagnosing a wide range of medical conditions. However, interpreting test results is not always straightforward. An abnormal test result does not always confirm the presence of a disease, just as a normal result does not guarantee its absence. To assess the reliability of these diagnostic tools, healthcare practitioners rely on two key statistical indicators: sensitivity and specificity.
Sensitivity is the...
699
Therapeutic Index01:13

Therapeutic Index

5.2K
The therapeutic index of a drug is a key parameter in pharmacology that quantifies the relative safety of a drug by calculating the ratio between the dose that causes toxicity in half the population (50%) to the dose that proves to be effective for half the population (50%). It provides a spectrum of doses for a particular drug ranging from effective to potentially toxic. To illustrate, consider an anticoagulant agent like warfarin. It possesses a narrow window within its therapeutic index to...
5.2K
Diagnostic and Statistical Manual of Mental Disorders (DSM)01:27

Diagnostic and Statistical Manual of Mental Disorders (DSM)

184
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...
184
Prediction Intervals01:03

Prediction Intervals

2.4K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y. 
2.4K

You might also read

Related Articles

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

Sort by
Same author

Who Is on the BIP Development Team for Students with IDD? A Case Study of One School District.

Behavior modification·2025
Same author

Estimating Bayesian Diagnostic Models with Attribute Hierarchies with the Hamiltonian-Gibbs Hybrid Sampler.

Multivariate behavioral research·2023
Same author

Longitudinal measurement invariance of the Working Alliance Inventory - Short form across coaching sessions.

BMC psychology·2022
Same author

Direct Estimation of Diagnostic Classification Model Attribute Mastery Profiles via a Collapsed Gibbs Sampling Algorithm.

Psychometrika·2022
Same author

Enabling Computer Adaptive Assessments for Slider-Bar Item Types with the Three-Part Beta Measurement Model.

Multivariate behavioral research·2022
Same author

Examining the psychometric properties of the Integrative Hope Scale's English translation in a mixed-diagnostic community health sample.

Psychiatric rehabilitation journal·2021
Same journal

Bayesian Machine Learning Tools for Alcohol Use Disorder Research: The bpaup R Package.

Multivariate behavioral research·2026
Same journal

A Unified Framework for Jointly modelling Response Times and Item Position Effects in Computer-Based Learning Assessments.

Multivariate behavioral research·2026
Same journal

Generalizability Theory Applied to Daily Relationship Quality: Substantive and Statistical Directions.

Multivariate behavioral research·2026
Same journal

A Modularized Higher-Order Diagnostic Classification Model for Clustered Attribute Hierarchies.

Multivariate behavioral research·2026
Same journal

Generalizing Causal Effects to a Target Population Without Individual-Level Data from the Target Population.

Multivariate behavioral research·2026
Same journal

betaselectr: Selective (and Proper) Standardization in Structural Equation Models.

Multivariate behavioral research·2026
See all related articles

Related Experiment Video

Updated: Sep 24, 2025

Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

861

Modification Indices for Diagnostic Classification Models.

Christy Brown1, Jonathan Templin2

  • 1Department of Education and Human Development, Clemson University.

Multivariate Behavioral Research
|May 4, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a new method to identify errors in diagnostic classification models (DCMs) and their Q-matrices. This computationally efficient technique helps refine educational assessments for better student mastery evaluation.

Keywords:
Diagnostic classification modelsQ-matrix misspecificationmodel selectionmodification indexone-sided score test

More Related Videos

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

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

Published on: January 11, 2020

7.6K
Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education
09:00

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

924

Related Experiment Videos

Last Updated: Sep 24, 2025

Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

861
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

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

Published on: January 11, 2020

7.6K
Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education
09:00

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

924

Area of Science:

  • Educational Measurement
  • Psychometrics
  • Statistical Modeling

Background:

  • Diagnostic Classification Models (DCMs) assess student mastery of skills.
  • Model or Q-matrix misspecification is a significant challenge in DCMs.
  • Current remediation options for misspecification are limited.

Purpose of the Study:

  • To define a computationally efficient, one-sided score statistic for detecting under-specification in DCMs.
  • To adapt modification indices from structural equation modeling for DCM analysis.
  • To provide a method for refining diagnostic models and Q-matrices.

Main Methods:

  • Defined a one-sided score statistic for item-level misspecification detection.
  • Utilized modification indices analogous to those in structural equation modeling.
  • Conducted a simulation study using a mixture reference distribution.

Main Results:

  • The proposed statistic (modification indices) demonstrated acceptable Type I error rates.
  • Modification indices effectively detected under-specified Q-matrices.
  • Sufficient power was observed for detecting omitted model parameters in large samples or with highly discriminating items.

Conclusions:

  • Modification indices offer a powerful tool for identifying and correcting misspecification in DCMs.
  • This method aids in the refinement of diagnostic models and Q-matrices.
  • The approach is applicable to large-scale diagnostic test data analysis.