Two simulations assessed the statistical bias, consistency, and efficiency of 4 different signal detection theory (SDT) sensitivity measures; a corrected-hit probability, the traditional d′ statistic, and 2 nonparametric measures collected from a collapsed-data procedure. Overall, results reinforce evidence that collapsed procedures produce relatively unbiased and efficient estimators. Recommendations for the best approach to using SDT for advertisement recognition testing are offered
