Compensatory selection is generally more reliable than multiple-hurdle selection. Yet, practitioners may lean toward multiple-hurdle models, because administering an entire predictor battery to every applicant can be time-consuming, labor-intensive, and costly. Using Monte Carlo simulation, we considered some specific cases to illustrate, in terms of selection utility and the cost-reliability tradeoff between compensatory and multiple-hurdle selection models. Results showed that compensatory model selection produced a higher level of expected criterion performance in the selected applicant subgroup, and a higher overall selection utility in most conditions. The simulation provides researchers and practitioners with a practical illustration of the tradeoff between reliable (compensatory) versus cost-efficient (multiple-hurdle) selection models – one that can inspire the exploration of other scenarios and tradeoffs.

中文翻译：

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人员选拔决策的效用

补偿选择通常比多障碍选择更可靠。然而，从业者可能倾向于多障碍模型，因为对每个申请人管理整个预测器电池可能是耗时，费力且昂贵的。使用蒙特卡洛模拟，我们考虑了一些特定情况，以选择效用以及补偿性和多障碍选择模型之间的成本可靠性权衡进行说明。结果表明，补偿模型的选择在所选申请人子组中产生了更高水平的预期标准性能，并且在大多数情况下产生了更高的总体选择效用。