A Taxonomy of Item Response Models

1986/12/01 by David Thissen, Lynne Steinberg · 420 citations
Computer Science · Decision Sciences · Mathematics · Psychology · #Advanced Statistical Modeling Techniques #Artificial intelligence #Categorical variable #Computer science #Econometrics #Item response theory #Machine learning #Mathematics #Multi-Criteria Decision Making #Psychology #Psychometric Methodologies and Testing #Psychometrics #Statistics #Taxonomy (biology)

paper · doi:10.1007/bf02295596

published in Psychometrika 51(4), 567-577 (Springer Science+Business Media)

openalex publication_date 1986/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/23

Abstract

A number of models for categorical item response data have been proposed in recent years. The models appear to be quite different. However, they may usefully be organized as members of only three distinct classes, within which the models are distinguished only by assumptions and constraints on their parameters. “Difference models” are appropriate for ordered responses, “divide-by-total” models may be used for either ordered or nominal responses, and “left-side added” models are used for multiple-choice responses with guessing. The details of the taxonomy and the models are described in this paper.

Citations

• A Rasch Model for Partial Credit Scoring
• Estimation of Latent Ability Using a Response Pattern of Graded Scores

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