Statistical Problems of Fitting Individual Growth Curves

Abstract

A thorough-going longitudinal study of a child’s growth can produce upward of forty observations spaced over the years from birth to maturity. Such a data record is too long and inevitably too noisy (because of measurement error and short-run growth variation) to be interpreted without some sort of condensation and smoothing. The length of the record forces attention to certain critical regions or features of the curve, but the noisiness of the data makes it risky to characterize these regions or features by a few isolated measurements. The only safe approach to interpretation of individual growth data is via a statistical method capable of revealing the essential trend and concisely describing its main features.