Several options are available for computing the most common score for the Implicit Association Test, the so-called D-score. 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 shiny package, a user-friendly, interactive, and open source web application (DscoreApp) has been created for the D-score computation. This app provides different options for computing the D-score algorithms and for applying different cleaning criteria. Beyond making the D-score 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 D-scores are immediately available and can be seen in easy-readable and interactive graphs, along with meaningful descriptive statistics. Graphical representations, data sets containing the D-scores, and other information on participants' performance are downloadable. In this work, the use of DscoreApp is illustrated on an empirical data set.
Epifania, M. O., Anselmi, P., Robusto, E., DscoreApp: A Shiny Web Application for the Computation of the Implicit Association Test D-Score, <<FRONTIERS IN PSYCHOLOGY>>, 2020; 10 (10): 2938-2948. [doi:10.3389/fpsyg.2019.02938] [https://hdl.handle.net/10807/231402]
DscoreApp: A Shiny Web Application for the Computation of the Implicit Association Test D-Score
Epifania, Marina Ottavia
;
2020
Abstract
Several options are available for computing the most common score for the Implicit Association Test, the so-called D-score. 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 shiny package, a user-friendly, interactive, and open source web application (DscoreApp) has been created for the D-score computation. This app provides different options for computing the D-score algorithms and for applying different cleaning criteria. Beyond making the D-score 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 D-scores are immediately available and can be seen in easy-readable and interactive graphs, along with meaningful descriptive statistics. Graphical representations, data sets containing the D-scores, and other information on participants' performance are downloadable. In this work, the use of DscoreApp is illustrated on an empirical data set.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.