TY - JOUR AU - Jekel, Marc AU - Nicklisch, Andreas AU - Glöckner, Andreas T1 - Implementation of the Multiple-Measure Maximum Likelihood strategy classification method in R JF - Judgment and Decision Making SP - 54 EP - 63 IS - 1 VL - 5 PY - 2010 UR - http://decisionsciencenews.com/sjdm/journal.sjdm.org/vol5.1.html AB - One major challenge to behavioral decision research is to identify the cognitive processes underlying judgment and decision making. Glöckner (2009) has argued that, compared to previous methods, process models can be more efficiently tested by simultaneously analyzing choices, decision times, and confidence judgments. The Multiple-Measure Maximum Likelihood (MM-ML) strategy classification method was developed for this purpose and implemented as already-to-use routine in STATA, a commercial package for statistical data analysis. In the present article, we describe the implementation of MM-ML in R, a free package for data analysis under the GNU general public license, and we provide a practical guide to application. We also provide MM-ML as an easy-to-use R function. Thus, prior knowledge of R programming is not necessary for those interested in using MM-ML. T4 - Addendum to Glöckner (2009) and practical guide for application Y3 - 26.11.2021 M4 - Citavi ER -