Department of Psychology, University of Massachusetts, 135 Hicks Way, Amherst, MA 01003-7710, USA.
Behav Res Methods. 2013 Sep;45(3):679-83. doi: 10.3758/s13428-012-0280-3.
Because the recorded location of an eyetracking fixation is not a perfect measure of the actual fixated location, the recorded fixation locations must be adjusted before analysis. Fixations are typically corrected manually. Making such changes, however, is time-consuming and necessarily involves a subjective component. The goal of this article is to introduce software to automate parts of the correction process. The initial focus is on the correction of vertical locations and the removal of outliers and ambiguous fixations in reading experiments. The basic idea behind the algorithm is to use linear regression to assign each fixation to a text line and to identify outliers. The freely available software is implemented as a function, , written in R.
由于眼动追踪仪记录的注视位置并不是实际注视位置的完美测量值，因此在分析之前必须对记录的注视位置进行调整。通常，注视点是手动修正的。然而，进行这些更改既耗时又必然涉及主观因素。本文的目的是介绍一种软件，以实现部分校正过程的自动化。初始重点是在阅读实验中校正垂直位置以及消除异常值和模糊注视点。该算法的基本思想是使用线性回归将每个注视点分配到一个文本行，并识别异常值。该免费软件作为一个函数实现， ，用 R 语言编写。
