ABSTRACT Eye tracking is widely used in developmental research to measure infants’ looking behavior before, during, or after particular events and can provide a measure of real-time processing. However, the dynamic time course of infants’ looking behaviors is rarely analyzed. Instead, eye tracking data is often averaged within a large window or is restricted to certain predictive or reactive looks before or after an event, which could conceal interesting looking patterns. In this article, we discuss an alternative approach using spline models – an approachable and informative method for analyzing how the trajectory of infants’ looking behaviors changes at discrete time points. We illustrate the benefits of spline models by demonstrating how to prepare, estimate, and interpret the results of a spline model in R and SAS, and we compare the results with an analysis of averaged looking times within a time window. We show that spline models can reveal patterns in the trajectory of participants’ looking that can be obscured by averaged looking times. Finally, we use a sensitivity analysis to show that spline models are reliable with small samples typical of developmental studies. Spline models can be useful to developmental researchers for analyzing the time course of event-based changes in eye tracking data.

中文翻译：

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使用样条模型分析眼动追踪数据中基于事件的变化

摘要眼动追踪广泛用于发育研究，以测量婴儿在特定事件之前、期间或之后的观看行为，并且可以提供实时处理的测量。然而，很少分析婴儿看行为的动态时间过程。相反，眼动追踪数据通常在一个大窗口内进行平均，或者仅限于某个事件之前或之后的某些预测或反应性外观，这可能会隐藏有趣的外观模式。在本文中，我们将讨论使用样条模型的另一种方法——一种易于理解且信息丰富的方法，用于分析婴儿观看行为的轨迹如何在离散时间点发生变化。我们通过演示如何在 R 和 SAS 中准备、估计和解释样条模型的结果来说明样条模型的好处，我们将结果与时间窗口内平均观看时间的分析进行比较。我们表明，样条模型可以揭示参与者观看轨迹中的模式，而这些模式可能会被平均观看时间所掩盖。最后，我们使用敏感性分析来证明样条模型对于发育研究中典型的小样本是可靠的。样条模型对于开发研究人员分析眼动追踪数据中基于事件的变化的时间过程非常有用。