Abstract
Several options are available for computing the most common score for the Implicit Association Test, the so-called <i>D-score</i>. However, all these options come with some drawbacks, related to either the need for a license, for being tailored on a specific administration procedure, or for requiring a degree of familiarity with programming. By using the R <b>shiny</b> package, a user-friendly, interactive, and open source web application (DscoreApp) has been created for the <i>D-score</i> computation. This app provides different options for computing the <i>D-score</i> algorithms and for applying different cleaning criteria. Beyond making the <i>D-score</i> computation easier, DscoreApp offers the chance to have an immediate glimpse on the results and to see how they change according to different settings configurations. The resulting <i>D-score</i>s are immediately available and can be seen in easy-readable and interactive graphs, along with meaningful descriptive statistics. Graphical representations, data sets containing the <i>D-score</i>s, and other information on participants' performance are downloadable. In this work, the use of DscoreApp is illustrated on an empirical data set.
Keywords
Computer scienceTest (biology)ComputationTest scoreSet (abstract data type)Web applicationAssociation (psychology)Information retrievalArtificial intelligenceWorld Wide WebPsychologyProgramming languageMathematics education
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Publication Info
- Year
- 2020
- Type
- article
- Volume
- 10
- Pages
- 2938-2938
- Citations
- 14
- Access
- Closed
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Cite This
Ottavia M. Epifania,
Pasquale Anselmi,
Egidio Robusto
(2020).
DscoreApp: A Shiny Web Application for the Computation of the Implicit Association Test D-Score.
Frontiers in Psychology
, 10
, 2938-2938.
https://doi.org/10.3389/fpsyg.2019.02938
Identifiers
- DOI
- 10.3389/fpsyg.2019.02938
- PMID
- 31998191
- PMCID
- PMC6968522