Molenaar Dylan, Bolsinova Maria
University of Amsterdam, The Netherlands.
Br J Math Stat Psychol. 2017 May;70(2):297-316. doi: 10.1111/bmsp.12087. Epub 2017 Feb 3.
In generalized linear modelling of responses and response times, the observed response time variables are commonly transformed to make their distribution approximately normal. A normal distribution for the transformed response times is desirable as it justifies the linearity and homoscedasticity assumptions in the underlying linear model. Past research has, however, shown that the transformed response times are not always normal. Models have been developed to accommodate this violation. In the present study, we propose a modelling approach for responses and response times to test and model non-normality in the transformed response times. Most importantly, we distinguish between non-normality due to heteroscedastic residual variances, and non-normality due to a skewed speed factor. In a simulation study, we establish parameter recovery and the power to separate both effects. In addition, we apply the model to a real data set.
在对反应和反应时间进行广义线性建模时,通常会对观察到的反应时间变量进行变换,使其分布近似正态。变换后的反应时间呈正态分布是可取的,因为这证明了基础线性模型中的线性和同方差性假设是合理的。然而,过去的研究表明,变换后的反应时间并不总是正态的。已经开发了一些模型来适应这种违背情况。在本研究中,我们提出了一种针对反应和反应时间的建模方法,以检验和模拟变换后反应时间的非正态性。最重要的是,我们区分了由于异方差残差方差导致的非正态性和由于速度因子偏斜导致的非正态性。在一项模拟研究中,我们确定了参数恢复情况以及区分这两种效应的功效。此外,我们将该模型应用于一个真实数据集。