Individual Differences and Fitting Methods for the Two-Choice Diffusion Model of Decision Making.
Individual Differences and Fitting Methods for the Two-Choice Diffusion Model of Decision Making.
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DOI：
10.1037/dec0000030
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发表时间：
2015-01-01
期刊：
影响因子：
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通讯作者：
Childers, Russ
中科院分区：
文献类型：
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作者：
Ratcliff, Roger;Childers, Russ
检查拟合扩散模型的方法，重点是该模型可以告诉我们有关个体差异的方法。从两个实验到数据，参数值，个体差异和实践效果的一致性从每个受试者的不同观测值检查中，从两个实验，个体差异和练习效应中获得了扩散模型参数。首先，研究了两个问题，可以获得各组之间的差异大小以区分组和第二个差异，第二个差异的差异大小，以找到相对于对照组缺乏赤字的单个受试者。实验中的参数值提供了模拟研究中用于检查个体差异的恢复的范围。这项研究使用了几种扩散模型拟合程序，拟合方法和已发布的软件包。在第二项仿真研究中，与不同的方法和偏差和循环模型参数中的标准偏差拟合了48组参数值（跨越从拟合到数据获得的典型值范围）的64组模拟数据（跨越典型值的范围）。方法。最后，在第三项模拟研究中，进行了标准卡方方法与分层贝叶斯方法之间的比较。这些研究的结果可以用作选择拟合方法的起点，也可以用作理解使用扩散模型分析来检查临床，神经心理学和教育测试中个体差异的优势的基础。
Methods of fitting the diffusion model were examined with a focus on what the model can tell us about individual differences. Diffusion model parameters were obtained from the fits to data from two experiments and consistency of parameter values, individual differences, and practice effects were examined using different numbers of observations from each subject. Two issues were examined, first, what sizes of differences between groups can be obtained to distinguish between groups and second, what sizes of differences would be needed to find individual subjects that had a deficit relative to a control group. The parameter values from the experiments provided ranges that were used in a simulation study to examine recovery of individual differences. This study used several diffusion model fitting programs, fitting methods, and published packages. In a second simulation study, 64 sets of simulated data from each of 48 sets of parameter values (spanning the range of typical values obtained from fits to data) were fit with the different methods and biases and standard deviations in recovered model parameters were compared across methods. Finally, in a third simulation study, a comparison between a standard chi-square method and a hierarchical Bayesian method was performed. The results from these studies can be used as a starting point for selecting fitting methods and as a basis for understanding the strengths and weaknesses of using diffusion model analyses to examine individual differences in clinical, neuropsychological, and educational testing.