The R package splithalf provides tools to estimate the internal consistency reliability of cognitive measures. In particular, the tools were developed for application to tasks that use difference scores as the main outcome measure, for instance the Stroop score or dot-probe attention bias index (average RT in incongruent trials minus average RT in congruent trials). The methods in splithalf are built around split half reliability estimation. To increase the robustness of these estimates, the package implements a permutation approach that takes a large number of random (without replacement) split halves of the data. For each permutation the correlation between halves is calculated, with the Spearman-Brown correction applied (Spearman, 1904). This process generates a distribution of reliability estimates from which we can extract and plot summary statistics (e.g. average and 95% HDI).
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Sam Parsons (2021) studied this question.
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