ArticlePsychometrika2018
Asymmetric Item Characteristic Curves and Item Complexity: Insights from Simulation and Real Data Analyses.
Article in Psychometrika, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- Joint modeling with generalized item response theory model family and response time model: Enhancing model structural flexibility and data-fitting adequacy.Behavior research methods · 2025Article
- Parsimonious item response theory modeling with the cauchit link: Revisiting the rationale of the four-parameter logistic model.Behavior research methods · 2025Article
- Parsimonious item response theory modeling with the negative log-log link: The role of inflection point shift.Behavior research methods · 2024Article
- Parsimonious asymmetric item response theory modeling with the complementary log-log link.Behavior research methods · 2023Article
- Identifying Ability and Nonability Groups: Incorporating Response Times Using Mixture Modeling.Educational and psychological measurement · 2022Article
- Two New Models for Item Preknowledge.Applied psychological measurement · 2022Article
- Exploring the Multiverse of Analytical Decisions in Scaling Educational Large-Scale Assessment Data: A Specification Curve Analysis for PISA 2018 Mathematics Data.European journal of investigation in health, psychology and education · 2022Article
- The Monotonic Polynomial Graded Response Model: Implementation and a Comparative Study.Applied psychological measurement · 2020Article
- A Psychometric Model for Discrete-Option Multiple-Choice Items.Applied psychological measurement · 2020Article
- Application of Asymmetric IRT Modeling to Discrete-Option Multiple-Choice Test Items.Frontiers in psychology · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
While item complexity is often considered as an item feature in test development, it is much less frequently attended to in the psychometric modeling of test items. Prior work suggests that item complexity may manifest through asymmetry in item characteristics curves (ICCs; Samejima in Psychometrika 65:319-335, 2000). In the current paper, we study the potential for asymmetric IRT models to inform empirically about underlying item complexity, and thus the potential value of asymmetric models as tools for item validation. Both simulation and real data studies are presented. Some psychometric consequences of ignoring asymmetry, as well as potential strategies for more effective estimation of asymmetry, are considered in discussion.
Indexed as
Identifiers
28948426What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.