Li Johnson Ching-Hong
Department of Psychology, University of Manitoba, Winnipeg, MB, Canada.
Front Psychol. 2018 Jun 13;9:883. doi: 10.3389/fpsyg.2018.00883. eCollection 2018.
In behavioral research, exploring bivariate relationships between variables and based on the concept of probability-of-superiority (PS) has received increasing attention. Unlike the conventional, linear-based bivariate relationship (e.g., Pearson's correlation), PS defines that and can be related based on their likelihood-e.g., a student who is above mean in SAT has 63% likelihood of achieving an above-mean college GPA. Despite its increasing attention, the concept of PS is restricted to a simple bivariate scenario (- pair), which hinders the development and application of PS in popular multivariate modeling such as structural equation modeling (SEM). Therefore, this study addresses an empirical-based simulation study that explores the potential of detecting PS-based relationship in SEM, called PS-SEM. The simulation results showed that the proposed PS-SEM method can detect and identify PS-based when data follow PS-based relationships, thereby providing a useful method for researchers to explore PS-based SEM in their studies. Conclusions, implications, and future directions based on the findings are also discussed.
在行为研究中，基于优势概率（PS）概念探索变量之间的双变量关系受到了越来越多的关注。与传统的基于线性的双变量关系（如皮尔逊相关性）不同，PS定义了变量之间可以基于其可能性相关——例如，SAT成绩高于平均水平的学生有63%的可能性获得高于平均水平的大学绩点。尽管PS受到了越来越多的关注，但其概念仅限于简单的双变量情形（一对变量），这阻碍了PS在诸如结构方程模型（SEM）等流行的多变量建模中的发展和应用。因此，本研究开展了一项基于实证的模拟研究，探索在SEM中检测基于PS的关系的潜力，即PS-SEM。模拟结果表明，当数据遵循基于PS的关系时，所提出的PS-SEM方法能够检测并识别基于PS的关系，从而为研究人员在其研究中探索基于PS的SEM提供了一种有用的方法。基于这些发现的结论、意义和未来方向也进行了讨论。
