A review of two different approaches for the analysis of growth data using longitudinal mixed linear models: comparing hierarchical linear regression (ML3, HLM) and repeated measures designs with structured covariance matrices (BMDP5V)

@inproceedings{Leeden1996ARO,
  title={A review of two different approaches for the analysis of growth data using longitudinal mixed linear models: comparing hierarchical linear regression (ML3, HLM) and repeated measures designs with structured covariance matrices (BMDP5V)},
  author={Rien van der Leeden and K. L. Vrijburg and Jan de Leeuw},
  year={1996}
}
Abstract In this paper we review two approaches for the analysis of growth data by means of longitudinal mixed linear models. In these models the individual growth parameters, (most often) specifying polynomial growth curves, may vary randomly across individuals. This variation may in turn be accounted for by explaining variables. The first approach we discuss, is a type of multilevel model in which growth data are treated as having a hierarchical structure: measurements are ‘nested’ within… CONTINUE READING

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