Wagenmakers Eric-Jan, van der Maas Han L J, Dolan Conor V, Grasman Raoul P P P
University of Amsterdam, Amsterdam, The Netherlands.
Psychon Bull Rev. 2008 Dec;15(6):1229-35. doi: 10.3758/PBR.15.6.1229.
In this rejoinder, we address two of Ratcliff's main concerns with respect to the EZ-diffusion model (Ratcliff, 2008). First, we introduce "robust-EZ," a mixture model approach to achieve robustness against the presence of response contaminants that might otherwise distort parameter estimates. Second, we discuss an extension of the EZ model that allows the estimation of starting point as an additional parameter. Together with recently developed, user-friendly software programs for fitting the full diffusion model (Vandekerckhove & Tuerlinckx, 2007; Voss & Voss, 2007), the development of the EZ model and its extensions is part of a larger effort to make diffusion model analyses accessible to a broader audience, an effort that is long overdue.
在本回应中,我们针对拉特克利夫对EZ扩散模型的两个主要担忧进行探讨(拉特克利夫,2008年)。首先,我们引入“稳健EZ”,这是一种混合模型方法,用于在存在可能扭曲参数估计的反应污染物的情况下实现稳健性。其次,我们讨论EZ模型的扩展,该扩展允许将起点估计作为一个额外参数。与最近开发的用于拟合完整扩散模型的用户友好型软件程序(万德克尔霍夫和图尔林克斯,2007年;沃斯和沃斯,2007年)一起,EZ模型及其扩展的开发是使扩散模型分析能够为更广泛的受众所用这一更大努力的一部分,这一努力早就该进行了。