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Repeated measures analysis of variance (rANOVA) is a commonly used statistical approach to repeated measure designs. [3] With such designs, the repeated-measure factor (the qualitative independent variable) is the within-subjects factor, while the dependent quantitative variable on which each participant is measured is the dependent variable.
In multilevel modeling for repeated measures data, the measurement occasions are nested within cases (e.g. individual or subject). Thus, level-1 units consist of the repeated measures for each subject, and the level-2 unit is the individual or subject. In addition to estimating overall parameter estimates, MLM allows regression equations at the ...
Sphericity can be evaluated when there are three or more levels of a repeated measure factor and, with each additional repeated measures factor, the risk for violating sphericity increases. If sphericity is violated, a decision must be made as to whether a univariate or multivariate analysis is selected. If a univariate method is selected, the ...
"Progress in analyzing repeated-measures data and its reflection in papers published in the archives of general psychiatry." Archives of General Psychiatry, 61, 310–317. Huck, S. W. & McLean, R. A. (1975). "Using a repeated measures ANOVA to analyze the data from a pretest-posttest design: A potentially confusing task".
Examples of all ANOVA and ANCOVA models with up to three treatment factors, including randomized block, split plot, repeated measures, and Latin squares, and their analysis in R (University of Southampton) NIST/SEMATECH e-Handbook of Statistical Methods, section 7.4.3: "Are the means equal?" Analysis of variance: Introduction
Further, they have their flexibility in dealing with missing values and uneven spacing of repeated measurements. [3] The Mixed model analysis allows measurements to be explicitly modeled in a wider variety of correlation and variance-covariance avoiding biased estimations structures.
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While the lowest level of data in multilevel models is usually an individual, repeated measurements of individuals may also be examined. [2] [4] As such, multilevel models provide an alternative type of analysis for univariate or multivariate analysis of repeated measures. Individual differences in growth curves may be examined. [2]