Miller J, van der Ham F, Sanders A F
Department of Psychology, University of Otago, Dunedin, New Zealand.
Acta Psychol (Amst). 1995 Nov;90(1-3):11-28. doi: 10.1016/0001-6918(95)00028-s.
Many experimental factors have been found to affect mean reaction time (RT) additively in factorial experiments. What sorts of RT models are compatible with this fact? Sternberg (1969) showed that serial, discrete-stage models are consistent with additivity, and as a result additivity has sometimes been regarded as evidence in favor of such models. However, McClelland (1979) showed that an alternative "cascade" model, which violates crucial assumptions of discrete-stage models, also predicts RT additivity in many cases. This article examines various modified versions of the cascade model, and shows that mean RT additivity arises from many overlapping stage models, including some with thresholds, information quantization, and nonlinear activation transformations. This suggests that other aspects of the data besides mean RT additivity should be examined to distinguish between serial and overlapping stage models.
在析因实验中，人们发现许多实验因素会对平均反应时（RT）产生累加影响。什么样的反应时模型与这一事实相符呢？斯滕伯格（1969年）指出，串行、离散阶段模型与累加性是一致的，因此累加性有时被视为支持此类模型的证据。然而，麦克莱兰（1979年）表明，另一种“级联”模型虽然违反了离散阶段模型的关键假设，但在许多情况下也能预测反应时的累加性。本文研究了级联模型的各种修正版本，并表明平均反应时的累加性源于许多重叠阶段模型，包括一些具有阈值、信息量化和非线性激活变换的模型。这表明，除了平均反应时的累加性之外，还应检查数据的其他方面，以区分串行和重叠阶段模型。
