Key points are not available for this paper at this time.
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 et al. (Fri,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: