Prior Distribution and Entropy in Computer Adaptive Testing Ability Estimation through MAP or EAP.

Joel Suárez-Cansino, Virgilio López-Morales, Luis Roberto Morales-Manilla, Adrián Alberto-Rodríguez, Julio César Ramos-Fernández

Abstract read

PubMed Full text at PMC Publisher

In one paragraph

Article in Entropy (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Joel Suárez-CansinoBasic Sciences and Engineering Institute, Systems and Information Technologies Research Center, Intelligent Computing Research Group, Autonomous University of Hidalgo State, Col. Carboneras, Mineral de la Reforma 42184, Hidalgo, Mexico.ORCID 0000-0002-8927-1135

Virgilio López-MoralesBasic Sciences and Engineering Institute, Systems and Information Technologies Research Center, Intelligent Computing Research Group, Autonomous University of Hidalgo State, Col. Carboneras, Mineral de la Reforma 42184, Hidalgo, Mexico.ORCID 0000-0003-2043-8766

Luis Roberto Morales-ManillaDepartment of Software Development, Advanced Computing and Innovation Research Group, Polytechnic University of Tulancingo, Tulancingo 43629, Hidalgo, Mexico.ORCID 0000-0003-4243-6155

Adrián Alberto-RodríguezBasic Sciences and Engineering Institute, Systems and Information Technologies Research Center, Intelligent Computing Research Group, Autonomous University of Hidalgo State, Col. Carboneras, Mineral de la Reforma 42184, Hidalgo, Mexico.ORCID 0000-0003-4854-6849

Julio César Ramos-FernándezDepartment of Mechatronics, Smart Technologies Applied to Social Development Research Group, Polytechnic University of Pachuca, Zempoala 43830, Hidalgo, Mexico.ORCID 0000-0002-9997-6550

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To derive a latent trait (for instance

Indexed as

Bayesian inferenceCATentropyexpectation a posterioriitem characteristic curveitem response theoryKullback–Leibler divergencelikelihood functionmaximum a posterioriperformance index function

Identifiers

PMID36673191

DOI10.3390/e25010050

PMCPMC9857967

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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.