Power of Models in Longitudinal Study: Findings From a Full-Crossed Simulation Design
Department of Quantitative Health Sciences
Medical Subject Headings
Longitudinal Studies; Models, Statistical; Computational Biology; Multivariate Analysis
Bioinformatics | Biostatistics | Epidemiology | Health Services Research
Because the power properties of traditional repeated measures and hierarchical multivariate linear models have not been clearly determined in the balanced design for longitudinal studies in the literature, the authors present a power comparison study of traditional repeated measures and hierarchical multivariate linear models under 3 variance-covariance structures. The results from a full-crossed simulation design suggest that traditional repeated measures have significantly higher power than do hierarchical multivariate linear models for main effects, but they have significantly lower power for interaction effects in most situations. Significant power differences are also exhibited when power is compared across different covariance structures.
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Citation: Journal of Experimental Education. 2009 Apr 1;77(3):215-254. Link to article on publisher's site
Fang, Hua; Brooks, Gordon P.; Rizzo, Maria L.; Espy, Kimberly Andrews; and Barcikowski, Robert S., "Power of Models in Longitudinal Study: Findings From a Full-Crossed Simulation Design" (2009). Quantitative Health Sciences Publications and Presentations. 869.