Multi-level models for longitudinal growth norms

Statistics in Medicine
H Pan, H Goldstein

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.

Citations

Sep 21, 2011·The International Journal of Biostatistics·Luc VillandréRobert W Platt
Sep 10, 2003·Annals of Human Biology·J Argyle
Jun 15, 2015·Journal of Clinical Epidemiology·Michael LawtonYoav Ben-Shlomo
Jun 30, 2007·Statistics in Medicine·Jenny ArgyleDavid A Wooff
Mar 6, 2012·Statistics in Medicine·J J StirnemannJ C Thalabard
Jan 10, 2002·Statistics in Medicine·Peter M HooperNestor N Demianczuk
Oct 11, 2013·Statistical Methods in Medical Research·Andrew J SimpkinKate Tilling
Dec 12, 2001·Stroke; a Journal of Cerebral Circulation·K TillingC D Wolfe
Nov 15, 2013·The American Journal of Clinical Nutrition·Jiajun XuYin Bun Cheung
Sep 29, 1999·Statistical Methods in Medical Research·E M Wright, P Royston

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