Analysis of Cohort Effects in Mixed Longitudinal Data Sets

Mixed longitudinal designs are among the most efficient for the study of growth and developmental processes. In this approach, one studies several (birth) cohorts, each for a relatively short length of time, and then links the growth curves for the individual cohorts together to obtain the growth curve for the entire length of time spanned by the ages of the subjects in all cohorts. Thus, e.g., in the Nijmegen Growth Study, three cohorts were each studied for 5 years, the intent being to join the three curves together to form a single curve covering the entire period from 4 to 14 years of age. In order for this approach to be valid, there either should be no cohort effects (secular trends) or the fitted curve must be adjusted in some way to correct for such effects if they exist. The question thus arises as to how one should test for the presence of cohort effects and what one should do about them if found. The problems which may arise using height and weight data from the Nijmegen Growth Study are illustrated. In particular for girls, height and weight both show cohort effects (at 9.25 years of age) when the raw data are used. If, however, the observed data are used to estimate the values at the target age, and these values are used in the comparison, differences between the cohorts are no longer significant. The problems are further illustrated using data from a mixed longitudinal data set of cleft lip and palate patients and data from the National Dutch Growth Study 1980.

Key words

ohort effects - mixed longitudinal design - growth studies