Mathematical models for the study of individual growth patterns.

The analysis of longitudinal growth data requires specific methodological approaches. One of the main goals of longitudinal growth studies is to establish individual growth patterns and to estimate, so-called, biological parameters of the growth curve, such as the timing and intensity of the adolescent growth spurt, for example. These features are providing us with information about the shape of the growth curve, rather than telling us what size is attained at a particular age. A basic technique to establish the continuous growth process from a set of discrete measurements of size in function of age is provided by curve fitting. Various models have been proposed to achieve this goal. They can mainly be subdivided into nonstructural and structural models. This paper deals with a description of some of the most commonly used models in the analysis of human growth data, emphasizing on their applicability in certain age periods and on the merits and limitation of the various approaches. Attention is also paid to a special type of nonstructural models based on longitudinal principal components analysis.