title: Multi-level models for longitudinal growth norms.
abstract: Multi-level models for estimating conditional and unconditional longitudinal growth norms are presented. The procedure involves transforming the original growth measurements to Normality and modelling these with a two-level random coefficient model. Growth norms for any desired time interval and function can be derived. Height and weight data are used for illustration.
authors.affiliation: Institute of Education, London, U.K.
authors.forename: H
authors.initials: H
authors.lastname: Pan
authors.forename: H
authors.initials: H
authors.lastname: Goldstein
mesh_terms: D000293:Adolescent; D000886:Anthropometry / Q000379:methods*; D001827:Body Height; D001835:Body Weight; D002648:Child; D002675:Child, Preschool; D006128:Growth / Q000502:physiology*; D006801:Humans; D016013:Likelihood Functions; D008137:Longitudinal Studies; D008297:Male; D015233:Models, Statistical; D012016:Reference Values; D012606:Scotland / Q000453:epidemiology