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  • 标题:Implementation of the Multiple-Measure Maximum Likelihood strategy classification method in R: Addendum to Gloeckner (2009) and practical guide for application
  • 本地全文:下载
  • 作者:Jekel, Marc ; Nicklisch, Andreas ; Gloeckner, Andreas
  • 期刊名称:Judgment and Decision Making
  • 印刷版ISSN:1930-2975
  • 出版年度:2010
  • 卷号:5
  • 期号:1
  • 页码:54-63
  • 出版社:Society for Judgment and Decision Making
  • 摘要:One major challenge to behavioral decision research is to identify the cognitive processes underlying judgment and decision making. Gloeckner (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 a ready-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.
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