DscoreApp

DscoreApp computes Implicit Association Test (IAT) D-scores to quantify implicit biases in psychological and social science research.

Key Features:

• Multiple computation algorithms: Supports various algorithms for calculating the IAT D-score to accommodate different analytic choices.
• Configurable data cleaning criteria: Applies diverse cleaning rules to reaction-time and trial-level data to produce robust D-score estimates.
• Immediate result visualization: Generates visual representations of computed D-scores to facilitate inspection of effects across conditions or groups.
• Descriptive statistics and graphical summaries: Produces summary statistics and graphical outputs that characterize participant performance and D-score distributions.

Scientific Applications:

• Implicit bias research: Enables computation and examination of IAT D-scores in studies of implicit attitudes in psychology, sociology, and cognitive science.
• Adaptation to diverse study designs: Accommodates varied computation methods and cleaning criteria, making it applicable across different IAT study designs and datasets.

Methodology:

Implements multiple algorithms for D-score calculation within an R environment using the R Shiny package, applies configurable data-cleaning criteria, and generates descriptive statistics and visualizations of results.