Coombs Aaron K, Hauenstein Neil M A
Department of Command, Leadership, and Management, United States Army War College, Carlisle, Pennsylvania.
Department of Psychology, Virginia Tech, Blacksburg, Virginia.
Mil Psychol. 2025 Jan 2;37(1):73-84. doi: 10.1080/08995605.2023.2300620. Epub 2024 Jan 2.
Elite military programs such as the 75th Ranger Regiment's Ranger Assessment and Selection Program (RASP) see rates of attrition often in excess of 50%, and amplify the need to identify and screen candidates based on their probability of successful matriculation. Models were developed (and cross-validated) to predict attrition from RASP using the physical abilities, cognitive abilities, and personality scores collected during candidate admissions screening. We report both regression weights and standardized odds ratios for optimum models of candidate success over three program timeframes to enable an understanding of the relative importance of each predictor. In spite of physical abilities scores being used to select RASP candidates, they were the strongest predictors of RASP attrition. Personality scores accounted for more variance in predicting candidate success than cognitive ability scores. Personality predictors, especially dimensions related to Openness, were better at predicting week one attrition than attrition in later weeks. The use of a single, aggregated candidate probability score for making admissions decisions is discussed, along with additional practical and scientific implications.
诸如第75游骑兵团的游骑兵评估与选拔计划(RASP)这样的精英军事项目,其淘汰率常常超过50%,这凸显了根据候选人成功入学的概率来识别和筛选他们的必要性。利用候选人入学筛选期间收集的体能、认知能力和个性得分,开发了(并进行了交叉验证)模型来预测RASP的淘汰情况。我们报告了三个项目时间框架内候选人成功的最佳模型的回归权重和标准化优势比,以便了解每个预测因素的相对重要性。尽管体能得分被用于选拔RASP候选人,但它们却是RASP淘汰的最强预测因素。在预测候选人成功方面,个性得分比认知能力得分解释了更多的方差。个性预测因素,尤其是与开放性相关的维度,在预测第一周的淘汰情况方面比预测后期几周的淘汰情况表现更好。文中讨论了使用单一的综合候选人概率得分来做出录取决定的情况,以及其他实际和科学意义。