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

Methods of Medium Optimization

Methods of Medium Optimization

Optimizing growth media enhances microbial proliferation and maximizes product yield. Statistical experimental design methodologies provide structured and reproducible approaches, offering progressively higher levels of robustness and efficiency.The One-Factor-at-a-Time (OFAT) MethodThe One-Factor-at-a-Time (OFAT) method involves adjusting a single variable while keeping all others constant. However, it cannot detect interactions between variables, often leading to suboptimal outcomes when...

Factorial Design

Factorial Design

Factorial Analysis is an experimental design that applies Analysis of Variance (ANOVA) statistical procedures to examine a change in a dependent variable due to more than one independent variable, also known as factors. Changes in worker productivity can be reasoned, for example, to be influenced by salary and other conditions, such as skill level. One way to test this hypothesis is by categorizing salary into three levels (low, moderate, and high) and skills sets into two levels (entry level...

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...

Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs

Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs

Bioequivalence experimental study designs play a pivotal role in testing the effectiveness of various treatments. Key among these are the repeated measures, cross-over, carry-over, and Latin square designs. In the repeated measures design, each subject receives all treatments, allowing for temporal comparisons. This type of design is useful in reducing variability but requires careful planning to avoid bias.The cross-over design, an economical method, involves sequential administration of...

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.

Reliability and Validity

Reliability and Validity

Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.

You might also read

Related Articles

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

Sort by

Same author

Modelling non-linear personality change surrounding transitions: A review of statistical approaches.

European journal of personality·2026

Same author

Bayes factor hypothesis testing in meta-analyses: Practical advantages and methodological considerations.

Research synthesis methods·2026

Same author

Rigid control of motor unit firing rates in the human tibialis anterior muscle persists during neurofeedback.

Journal of neurophysiology·2026

Same author

To vary or not to vary: A flexible empirical Bayes factor for testing variance components.

The British journal of mathematical and statistical psychology·2026

Same author

Assessing mobile instant messenger networks with donated data.

Social network analysis and mining·2026

Same author

A tutorial on Bayesian hypothesis testing of correlation coefficients using the BFpack-module in JASP.

Behavior research methods·2025

Search research articles

Related Experiment Video

Updated: Jun 16, 2026

Computerized Adaptive Testing System of Functional Assessment of Stroke

Computerized Adaptive Testing System of Functional Assessment of Stroke

Published on: January 7, 2019

Multidimensional Adaptive Testing with Optimal Design Criteria for Item Selection.

Joris Mulder¹, Wim J van der Linden

¹Department of Research Methodology, Measurement, and Data Analysis, Twente University, P.O. Box 217, 7500 AE Enschede, The Netherlands.

|February 2, 2010

Summary

This summary is machine-generated.

This study evaluates optimal design criteria for multidimensional adaptive testing. A-optimality and D-optimality are best for intentional abilities, while c-optimality suits composite ability measurement.

More Related Videos

Advancing Dyslexia Assessment in Children Through Computerized Testing

Advancing Dyslexia Assessment in Children Through Computerized Testing

Published on: August 16, 2024

Related Experiment Videos

Last Updated: Jun 16, 2026

Computerized Adaptive Testing System of Functional Assessment of Stroke

Computerized Adaptive Testing System of Functional Assessment of Stroke

Published on: January 7, 2019

Advancing Dyslexia Assessment in Children Through Computerized Testing

Advancing Dyslexia Assessment in Children Through Computerized Testing

Published on: August 16, 2024

Area of Science:

Psychometrics
Statistical modeling
Educational measurement

Background:

Multidimensional adaptive testing (MAT) requires robust item selection criteria.
Optimal design theory offers potential criteria but requires adaptation for MAT.

Purpose of the Study:

To evaluate various optimal design criteria for item selection in MAT scenarios.
To determine the most effective criteria based on different testing objectives (all intentional abilities, nuisance abilities, composite abilities).

Main Methods:

Theoretical analysis of optimality criteria.
Simulation studies using generated data to assess criterion performance.
Evaluation of criteria based on estimation accuracy and item parameter preferences.

Main Results:

A-optimality and D-optimality provide the most accurate estimates when all abilities are intentional.
E-optimality is not recommended due to erratic behavior in MAT.
A(s)-optimality or D(s)-optimality are recommended when some abilities are considered nuisances.
c-optimality is most effective for measuring a linear combination of abilities.
Criteria differ in their preference for items based on discrimination parameter values.

Conclusions:

The choice of optimality criterion significantly impacts estimation accuracy in MAT.
Specific criteria are better suited for different MAT objectives.
Understanding item parameter preferences aids in criterion selection for optimal test design.