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On growth curves and mixture models
Author(s) -
Hoeksma Jan B.,
Kelderman Henk
Publication year - 2006
Publication title -
infant and child development
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.87
H-Index - 57
eISSN - 1522-7219
pISSN - 1522-7227
DOI - 10.1002/icd.483
Subject(s) - inference , growth model , extension (predicate logic) , population , sample (material) , econometrics , trajectory , growth curve (statistics) , population growth , mixture model , psychology , artificial intelligence , computer science , mathematics , mathematical economics , sociology , demography , chromatography , astronomy , programming language , chemistry , physics
The multilevel model of change and the latent growth model are flexible means to describe all sorts of population heterogeneity with respect to growth and development, including the presence of sub‐populations. The growth mixture model is a natural extension of these models. It comes at hand when information about sub‐populations is missing and researchers nevertheless want to retrieve developmental trajectories from sub‐populations. We argue that researchers have to make rather strong assumptions about the sub‐populations or latent trajectory classes in order to retrieve existing population differences. A simulated example is discussed, showing that a sample of repeated measures drawn from two sub‐populations easily leads to the mistaken inference of three sub‐populations, when assumptions are not met. The merits of methodological advises on this issue are discussed. It is concluded that growth mixture models should be used with understanding, and offer no free way to growth patterns in unknown sub‐populations. Copyright © 2006 John Wiley & Sons, Ltd.