Coertjens Liesje, Donche Vincent, De Maeyer Sven, Vanthournout Gert, Van Petegem Peter
Psychological Sciences Research Institute, Université Catholique de Louvain, Louvain-la-Neuve, Belgium.
Department of Educational Sciences, Faculty of Social Sciences, University of Antwerp, Antwerp, Belgium.
PLoS One. 2017 Sep 13;12(9):e0182615. doi: 10.1371/journal.pone.0182615. eCollection 2017.
Longitudinal data is almost always burdened with missing data. However, in educational and psychological research, there is a large discrepancy between methodological suggestions and research practice. The former suggests applying sensitivity analysis in order to the robustness of the results in terms of varying assumptions regarding the mechanism generating the missing data. However, in research practice, participants with missing data are usually discarded by relying on listwise deletion. To help bridge the gap between methodological recommendations and applied research in the educational and psychological domain, this study provides a tutorial example of sensitivity analysis for latent growth analysis. The example data concern students' changes in learning strategies during higher education. One cohort of students in a Belgian university college was asked to complete the Inventory of Learning Styles-Short Version, in three measurement waves. A substantial number of students did not participate on each occasion. Change over time in student learning strategies was assessed using eight missing data techniques, which assume different mechanisms for missingness. The results indicated that, for some learning strategy subscales, growth estimates differed between the models. Guidelines in terms of reporting the results from sensitivity analysis are synthesised and applied to the results from the tutorial example.
纵向数据几乎总是存在缺失数据的问题。然而，在教育和心理学研究中，方法学建议与研究实践之间存在很大差异。前者建议进行敏感性分析，以便在关于缺失数据产生机制的不同假设下检验结果的稳健性。然而，在研究实践中，有缺失数据的参与者通常通过依单变量删除法被剔除。为了弥合教育和心理学领域方法学建议与应用研究之间的差距，本研究提供了一个潜在增长分析敏感性分析的示例教程。示例数据涉及高等教育阶段学生学习策略的变化。比利时一所大学学院的一组学生被要求在三个测量阶段完成《学习风格量表简版》。每次都有相当数量的学生未参与。使用八种缺失数据技术评估学生学习策略随时间的变化，这些技术假设了不同的缺失机制。结果表明，对于一些学习策略子量表，不同模型的增长估计有所不同。综合了敏感性分析结果报告方面的指导方针，并将其应用于示例教程的结果。
