Evidence map›Paper›PMID 40913152›Full record

ArticleBehavior research methods2025

An introduction to the Item Response Warehouse (IRW): A resource for enhancing data usage in psychometrics.

Benjamin W Domingue, Mika Braginsky, Lucy Caffrey-Maffei, Joshua B Gilbert, Klint Kanopka, Radhika Kapoor, Hansol Lee, Yiqing Liu, Savira Nadela, Guanzhong Pan and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Behavior research methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Benjamin W DomingueStanford University, Stanford, CA, USA. ben.domingue@gmail.com.
Mika BraginskyStanford University, Stanford, CA, USA.
Lucy Caffrey-MaffeiStanford University, Stanford, CA, USA.
Joshua B GilbertHarvard University, Cambridge, Massachusetts, USA.
Klint KanopkaNew York University, New York, USA.
Radhika KapoorStanford University, Stanford, CA, USA.
Hansol LeeStanford University, Stanford, CA, USA.
Yiqing LiuStanford University, Stanford, CA, USA.
Savira NadelaStanford University, Stanford, CA, USA.
Guanzhong PanThe University of Edinburgh, Edinburgh, UK.
Lijin ZhangStanford University, Stanford, CA, USA.
Susu ZhangUniversity of Illinois Urbana-Champaign, Urbana-Champaign, Illinois, USA.
Michael C FrankStanford University, Stanford, CA, USA.

Funding

Institute of Education Sciences R305D240025
6 · The paper itself

Abstract

The Item Response Warehouse (IRW) is a collection and standardization of a large volume of item response datasets in a free and open-source platform for researchers. We describe key elements of the data standardization process and provide a brief description of the over 900 datasets in the current iteration of the IRW (version 28.2). We describe how to access the data through both the website and an API, and offer a brief tutorial with example R code illustrating how to download data from the IRW and use it in standard psychometric analyses. While we are continuing to develop the IRW, this presentation may help researchers utilize data from this resource for work in psychometrics and related fields.

Indexed as

Databases, FactualPsychometricsHumansBig dataFactor analysisItem response theoryMeasurementPsychometrics

Identifiers

PMID40913152
PMCPMC12413415

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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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.