Evidence map›Paper›PMID 30120265›Full record

ArticleScientific reports2018

Development and Validation of the Computerised Adaptive Beat Alignment Test (CA-BAT).

Peter M C Harrison, Daniel Müllensiefen

Abstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 4 pooled it
–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

39 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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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

2 authors.

Peter M C HarrisonSchool of Electronic Engineering and Computer Science, Queen Mary University of London, London, E1 4NS, United Kingdom. p.m.c.harrison@qmul.ac.uk.ORCID 0000-0002-9851-9462
Daniel MüllensiefenDepartment of Psychology, Goldsmiths, University of London, London, SE14 6NW, United Kingdom.

Funding

Engineering and Physical Sciences Research Council (EPSRC) EP/L01632X/1
6 · The paper itself

Abstract

Beat perception is increasingly being recognised as a fundamental musical ability. A number of psychometric instruments have been developed to assess this ability, but these tests do not take advantage of modern psychometric techniques, and rarely receive systematic validation. The present research addresses this gap in the literature by developing and validating a new test, the Computerised Adaptive Beat Alignment Test (CA-BAT), a variant of the Beat Alignment Test (BAT) that leverages recent advances in psychometric theory, including item response theory, adaptive testing, and automatic item generation. The test is constructed and validated in four empirical studies. The results support the reliability and validity of the CA-BAT for laboratory testing, but suggest that the test is not well-suited to online testing, owing to its reliance on fine perceptual discrimination.

Indexed as

Models, TheoreticalAdaptation, PsychologicalAlgorithmsHumansPsychometrics

Identifiers

PMID30120265
PMCPMC6097996

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.