Soto Fabian A, Zheng Emily, Fonseca Johnny, Ashby F Gregory
Department of Psychology, Florida International University, MiamiFL, USA.
Department of Statistics and Applied Probability, University of California, Santa Barbara, Santa BarbaraCA, USA.
Front Psychol. 2017 May 23;8:696. doi: 10.3389/fpsyg.2017.00696. eCollection 2017.
Determining whether perceptual properties are processed independently is an important goal in perceptual science, and tools to test independence should be widely available to experimental researchers. The best analytical tools to test for perceptual independence are provided by General Recognition Theory (GRT), a multidimensional extension of signal detection theory. Unfortunately, there is currently a lack of software implementing GRT analyses that is ready-to-use by experimental psychologists and neuroscientists with little training in computational modeling. This paper presents , an R package developed with the explicit aim of providing experimentalists with the ability to perform full GRT analyses using only a couple of command lines. We describe the software and provide a practical tutorial on how to perform each of the analyses available in . We also provide advice to researchers on best practices for experimental design and interpretation of results when applying GRT and .
确定感知属性是否独立处理是感知科学中的一个重要目标，用于测试独立性的工具应该可供实验研究人员广泛使用。用于测试感知独立性的最佳分析工具由通用识别理论（GRT）提供，它是信号检测理论的多维扩展。不幸的是，目前缺乏可供实验心理学家和神经科学家使用的、只需很少计算建模培训就能直接使用的实施GRT分析的软件。本文介绍了 ，这是一个R包，开发的明确目的是让实验人员只需使用几条命令行就能执行完整的GRT分析。我们描述了该软件，并提供了一个实用教程，介绍如何执行 中可用的每种分析。我们还就应用GRT和 时实验设计和结果解释的最佳实践向研究人员提供建议。
