The use of descriptive statistics in pilot testing procedures requires objective, standard diagnostic tools that are feasible for small sample sizes. While current psychometric practices report item-level statistics, they often report these raw descriptives separately rather than consolidating both mean and standard deviation into a single diagnostic tool to directly measure item quality. By leveraging the analytical properties of Cohen's d, this article repurposes its use in scale development as a standardized item deviation index. This measures the extent of an item's raw deviation relative to its scale midpoint while accounting for its own uncertainty. Analytical properties such as boundedness, scale invariance, and bias are explored to further understand how the index values behave, which will aid future efforts to establish empirical thresholds that characterize redundancy among formative indicators and consistency among reflective indicators.

翻译：在预测试程序中使用描述性统计需要客观、标准的诊断工具，且适用于小样本量。当前的心理测量实践虽然报告项目级统计量，但通常单独报告这些原始描述性统计，而非将均值和标准差整合为单一诊断工具以直接衡量项目质量。本文利用Cohen's d的分析特性，将其在量表开发中的用途重新定位为标准化项目偏差指数。该指数在考虑项目自身不确定性的同时，衡量项目原始偏差相对于量表中间点的程度。通过探究有界性、尺度不变性和偏差等分析特性，进一步理解指数值的行为特征，这将有助于未来建立经验阈值，以描述形成性指标间的冗余性和反映性指标间的一致性。