Applying Linear Mixed Effects Models (LMMs) in Within-Participant Designs With Subjective Trial-Based Assessments of Awareness—a Caveat

Frontiers in Psychology

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