The overconstraint of response time models: Rethinking the scaling problem
The overconstraint of response time models: Rethinking the scaling problem
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DOI：
10.3758/pbr.16.6.1129
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发表时间：
2009-12-01
影响因子：
3.5
通讯作者：
Heathcote, Andrew
中科院分区：
文献类型：
--
作者：
Donkin, Chris;Brown, Scott D.;Heathcote, Andrew
选择反应时间(RT)理论提供了对简单决定的心理基础的洞察。证据积累(或序贯抽样)模型是最成功的选择理论。这些模型都具有相同的“比例”属性--它们的参数子集可以乘以相同的量，而不会改变它们的预测。此属性意味着必须固定单个参数才能估计其余参数。在这篇文章中，我们表明，这个问题的传统解决方案已经过度约束了这些模型，不必要地限制了它们解释数据的能力，并做出了隐含的--因此未经检验的--心理学假设。我们表明，即使考虑到增加的模型复杂性，这些模型的版本以最小的方式解决了缩放问题，可以比它们的过度约束的对应模型提供更好的数据描述。
Theories of choice response time (RT) provide insight into the psychological underpinnings of simple decisions. Evidence accumulation (or sequential sampling) models are the most successful theories of choice RT These models all have the same "scaling" property-that a subset of their parameters can be multiplied by the same amount without changing their predictions. This property means that a single parameter must be fixed to allow the estimation of the remaining parameters. In the present article, we show that the traditional solution to this problem has overconstrained these models, unnecessarily restricting their ability to account for data and making implicit-and therefore unexamined-psychological assumptions. We show that versions of these models that address the scaling problem in a minimal way can provide a better description of data than can their overconstrained counterparts, even when increased model complexity is taken into account.