The Science and Practice of Item Response Theory in Organizations
Bibliographic Data
| ID | 15735528 |
|---|---|
| Authors | Jonas W B Lang (0000-0003-1115-3443, University of Exeter, corresponding author), Louis Tay (0000-0002-5522-4728, Purdue University West Lafayette) |
| Year | 2020 |
| Volume | 8 |
| Issue | 1 |
| Pages | 311-338 |
| Publication date | 2020-11-12 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Annual Review of Organizational Psychology and Organizational Behavior (JOURNAL) |
| Journal identifiers | ISSN: 2327-0608 • E-ISSN: 2327-0616 |
| Publisher | Annual Reviews (PUBLISHER • US) |
| DOI | 10.1146/annurev-orgpsych-012420-061705 |
| OpenAlex | W3105143771 |
| Language | EN |
| Citations received | 5 |
| References cited | 116 |
Item response theory (IRT) is a modeling approach that links responses to test items with underlying latent constructs through formalized statistical models. This article focuses on how IRT can be used to advance science and practice in organizations. We describe established applications of IRT as a scale development tool and new applications of IRT as a research and theory testing tool that enables organizational researchers to improve their understanding of workers and organizations. We focus on IRT models and their application in four key research and practice areas: testing, questionnaire responding, construct validation, and measurement equivalence of scores. In so doing, we highlight how novel developments in IRT such as explanatory IRT, multidimensional IRT, random item models, and more complex models of response processes such as ideal point models and tree models can potentially advance existing science and practice in these areas. As a starting point for readers interested in learning IRT and applying recent developments in IRT in their research, we provide concrete examples with data and R code
Construct (python library · Data science · Equivalence (formal languages · Item response theory · Management science · Psychometrics · Statistics · Advanced Statistical Modeling Techniques · Computer Science · Engineering · Mathematics · Psychometric Methodologies and Testing · Reliability and Agreement in Measurement
Statistical Theories of Mental Test Scores
Handbook of Modern Item Response Theory
Measurement Theory
Test Equating, Scaling, and Linking
Theory of mental tests.
Explanatory Item Response Models
Multidimensional Item Response Theory
The measurement of intelligence.
Economic Choices
The Concept of Validity.
Coefficients Alpha, Beta, Omega, and the glb
A law of comparative judgment.
LTM
The linear logistic test model as an instrument in educational research
Mirt
Balancing Type I error and power in linear mixed models
The Attack of the Psychometricians
On the Use, the Misuse, and the Very Limited Usefulness of Cronbach’s Alpha
A Review and Synthesis of the Measurement Invariance Literature
Random effects structure for confirmatory hypothesis testing
Fitting Linear Mixed-Effects Models Using lme4
Applications of the Linear Logistic Test Model in Psychometric Research
Item Response Theory With Covariates (IRT-C)
Item Response Modeling of Paired Comparison and Ranking Data
Dissociating Indifferent, Directional, and Extreme Responding in Personality Data
Methodological issues for building item banks and computerized adaptive scales
Computerized Adaptive Testing for Effective and Efficient Measurement in Counseling and Education
The Dark Triad of personality
Clinical outcome measurement
Meaning and Values in Test Validation
Psychometric Evaluation and Calibration of Health-Related Quality of Life Item Banks
Postscript
Practical Issues in Implementing and Understanding Bayesian Ideal Point Estimation
Biased test items and differential validity
Attitudes Can Be Measured
| Unique citing works | 5 |
|---|---|
| Citations per year | 1 |
| Citation span | 2021 - 2025 (5) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 5 |