Department of Management, College of Business, University of Colorado at Colorado Springs, Colorado Springs, CO 80918, USA.
J Appl Psychol. 2013 May;98(3):454-68. doi: 10.1037/a0031909. Epub 2013 Mar 4.
We explored whether voluntary survey completion by team members (in aggregate) is predictable from team members' collective evaluations of team-emergent states. In doing so, we reanalyze less-than-complete survey data on 110 teams from a published field study, using so-called traditional and modern missing data techniques to probe the sensitivity of these team-level relationships to data missingness. The multivariate findings revealed that a greater within-team participation rate was indeed related to a higher team-level (mean) score on team mental efficacy (across all four missing-data techniques) and less dispersion among team member judgments about internal cohesion (when the 2 modern methods were used). In addition, results show that a commonly used approach of retaining only those teams with high participation rates produces inflated standardized effect size (i.e., R²) estimates and decreased statistical power. Suggestions include research design considerations and a comprehensive methodology to account for team member data missingness.
我们探讨了团队成员（总体而言）自愿完成调查的情况是否可以从团队成员对团队出现的状态的集体评估中预测到。为此，我们重新分析了一项已发表的实地研究中关于 110 个团队的不完整调查数据，使用所谓的传统和现代缺失数据技术来探测这些团队层面关系对数据缺失的敏感性。多元分析结果表明，团队内部参与率越高，团队精神效能的团队层面（平均）得分确实越高（所有四种缺失数据技术都是如此），团队成员对内部凝聚力的判断差异越小（当使用 2 种现代方法时）。此外，结果表明，常用的仅保留高参与率团队的方法会导致夸大标准化效应量（即 R²）估计值和降低统计能力。建议包括研究设计考虑因素和一种全面的方法来考虑团队成员数据缺失的问题。
