Unit-weight sum scores (UWSSs) are routinely used as estimates of factor scores on the basis of solutions obtained with the nonlinear exploratory factor analysis (EFA) model for ordered-categorical responses. Theoretically, this practice results in a loss of information and accuracy, and is expected to lead to biased estimates. However, the practical relevance of these limitations is far from clear. In this article, we adopt an empirical view and propose indices and procedures (some of them new) for assessing the appropriateness of UWSSs in nonlinear EFA applications. A new automated approach for obtaining UWSSs that maximize fidelity and correlational accuracy is proposed. The appropriateness of UWSSs under different conditions and the behavior of the present proposal in comparison with other more common approaches are assessed with a simulation study. A tutorial for interested practitioners is presented using an illustrative example based on a well-known personality questionnaire. All the procedures proposed in the article have been implemented in a well-known noncommercial EFA program.

单位权重总得分 (UWSS) 通常用作因子得分的估计，其基础是通过有序分类响应的非线性探索性因子分析 (EFA) 模型获得的解。从理论上讲，这种做法会导致信息和准确性的损失，并预计会导致估计有偏差。然而，这些限制的实际意义还远不清楚。在本文中，我们采用实证观点并提出了用于评估 UWSS 在非线性 EFA 应用中的适用性的指标和程序（其中一些是新的）。提出了一种新的自动化方法来获取 UWSS，最大限度地提高保真度和相关精度。通过模拟研究评估了 UWSS 在不同条件下的适用性以及本提案与其他更常见方法相比的行为。使用基于众所周知的性格调查问卷的说明性示例为感兴趣的从业者提供了教程。本文提出的所有程序均已在一个著名的非商业性全民教育计划中得到实施。