期刊论文详细信息
Frontiers in Psychology | |
Applying Linear Mixed Effects Models (LMMs) in Within-Participant Designs With Subjective Trial-Based Assessments of Awarenessâa Caveat | |
Guido Hesselmann1  | |
关键词: post hoc trial sorting; anova; linear mixed models; unbalanced data; visibility; consciousness; awareness; | |
DOI : 10.3389/fpsyg.2018.00788 | |
学科分类:心理学(综合) | |
来源: Frontiers | |
【 摘 要 】
In experimental psychology, including consciousness research, within-participant designs are typically more powerful than between-participant designs. During the last decades or so, the most widely used statistical method to analyze data from within-participant designs has been the repeated-measures (rm-) ANOVA. In recent years, however, empirical studies have increasingly turned toward using linear mixed effects models (LMM) to analyze data from within-participant designs (Baayen et al., 2008; Magezi, 2015).
【 授权许可】
CC BY
【 预 览 】
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