Schmitt Neal, Oswald Frederick L, Kim Brian H, Imus Anna, Merritt Stephanie, Friede Alyssa, Shivpuri Smriti
Department of Psychology, Michigan State University, East Lansing, MI 48824-1116, USA.
J Appl Psychol. 2007 Jan;92(1):165-79. doi: 10.1037/0021-9010.92.1.165.
To determine whether profiles of predictor variables provide incremental prediction of college student outcomes, the authors 1st applied an empirical clustering method to profiles based on the scores of 2,771 entering college students on a battery of biographical data and situational judgment measures, along with SAT and American College Test scores and high school grade point average, which resulted in 5 student groups. Performance of the students in these clusters was meaningfully different on a set of external variables, including college grade point average, self-rated performance, class absenteeism, organizational citizenship behavior, intent to quit their university, and satisfaction with college. The 14 variables in the profile were all significantly correlated with 1 or more of the outcome measures; however, nonlinear prediction of these outcomes on the basis of cluster membership did not add incrementally to a linear-regression-based combination of these 14 variables as predictors.
为了确定预测变量的概况是否能对大学生的结果提供增量预测，作者首先基于2771名入学大学生在一系列传记数据和情境判断测试中的得分，以及学术能力评估测试（SAT）、美国大学考试（ACT）成绩和高中平均绩点，对概况应用了一种实证聚类方法，结果得到了5个学生群体。在包括大学平均绩点、自我评定表现、课堂缺勤率、组织公民行为、退学意愿和对大学的满意度等一组外部变量上，这些聚类中的学生表现存在显著差异。概况中的14个变量均与1个或更多结果指标显著相关；然而，基于聚类成员身份对这些结果进行非线性预测，并没有在将这14个变量作为预测指标的基于线性回归的组合基础上增加增量预测。
