快速命名的非总时间测量：暂停时间变异性和任务长度能否改进预测

Purpose: Although rapid automatized naming (RAN) is typically measured by the total time to name an array of items, more precise methods may be needed to capture the full range of processes underlying RAN—including pause time, a component of total time that reflects response preparation before the articulation of each item. This study investigated whether two underexplored aspects of RAN—pause time variability (PTV) and task length—can improve or streamline the prediction of future reading difficulties. Using mixed-effects location scale models (MELSMs), which capture item-by-item variability