Testing for suspected impairments and dissociations in single-case studies in neuropsychology: Evaluation of alternatives using Monte Carlo simulations and revised tests for dissociations
Testing for suspected impairments and dissociations in single-case studies in neuropsychology: Evaluation of alternatives using Monte Carlo simulations and revised tests for dissociations
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DOI：
10.1037/0894-4105.19.3.318
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发表时间：
2005-05-01
期刊：
影响因子：
2.4
通讯作者：
Garthwaite, PH
中科院分区：
文献类型：
--
作者：
Crawford, JR;Garthwaite, PH
在神经心理学的单例研究中，将一个病人与一个小的对照样本进行比较。检验任务X上的缺陷或任务X和Y之间的显著差异的方法，要么将控制样本统计量作为参数（使用z和z(D)），要么使用修改的t检验。蒙特卡罗模拟表明，如果使用z来测试赤字，则对于小的控制样本，I型错误率很高，而对于修改的t检验，错误率的控制基本上是完美的。对差异测试的模拟显示，z(D)的错误率非常高。一种新的差异测试方法（修订后的标准化差异测试）可以很好地控制错误率，即使样本量很小。实现这种新测试的计算机程序（并应用标准来测试经典和强解离）是可用的。
In neuropsychological single-case studies, a patient is compared with a small control sample. Methods of testing for a deficit on Task X, or a significant difference between Tasks X and Y, either treat the control sample statistics as parameters (using z and z(D)) or use modified t tests. Monte Carlo simulations demonstrated that if z is used to test for a deficit, the Type I error rate is high for small control samples, whereas control of the error rate is essentially perfect for a modified t test. Simulations on tests for differences revealed that error rates were very high for z(D). A new method of testing for a difference (the revised standardized difference test) achieved good control of the error rate, even with very small sample sizes. A computer program that implements this new test (and applies criteria to test for classical and strong dissociations) is made available.