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January 2022

Analysis of longitudinal data using the hierarchical linear model

Journal/Book: Qual Quant. 1996; 30: Spuiboulevard 50, PO Box 17, 3300 AA Dordrecht, Netherlands. Kluwer Academic Publ. 405-426.

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.

Note: Article Snijders T, Univ Groningen, ICs Dept Stat & Measurement Theory, Grote Kruisstr 21-1, NL-9712 Ts Groningen, NETHERLANDS

Keyword(s): multilevel analysis; hierarchical linear model; random coefficients; PSYCHOLOGICAL DISTRESS; GROWTH; TIME


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