Abstract
The hierarchical linear model in a linear model with nested random coefficients, fruitfully used for multilevel research. A tutorial is presented on the use of this model for the analysis of longitudinal data, i.e., repeated data on the same subjects. An important advantage of this approach is that differences across subjects in the numbers and spacings of measurement occasions do not present a problem, and that changing covariates can easily be handled. The tutorial approaches the longitudinal data as measurements on populations of (subject-specific) functions.
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Snijders, T. Analysis of longitudinal data using the hierarchical linear model. Qual Quant 30, 405–426 (1996). https://doi.org/10.1007/BF00170145
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DOI: https://doi.org/10.1007/BF00170145