Optimal Experimental Design for Model Discrimination

被引:92
作者
Myung, Jay I. [1 ]
Pitt, Mark A. [1 ]
机构
[1] Ohio State Univ, Dept Psychol, Columbus, OH 43210 USA
基金
美国国家卫生研究院;
关键词
formal modeling; model discrimination; Markov chain Monte Carlo; retention; categorization;
D O I
10.1037/a0016104
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
Models of a psychological process can be difficult to discriminate experimentally because it is not easy to determine the values of the critical design variables (e.g., presentation schedule, Stimulus structure) that will be most informative in differentiating them. Recent developments in sampling-based search methods in statistics make it possible to determine these values and thereby identify an optimal experimental design. After describing the method, it is demonstrated in 2 content areas in cognitive psychology in which models are highly competitive: retention (i.e., forgetting) and categorization. The optimal design is compared with the quality of designs used in the literature. The findings demonstrate that design optimization has the potential to increase the informativeness of the experimental method.
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页码:499 / 518
页数:20
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