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Most growth studies to date have been based on either cross-sectional or longitudinal designs despite the fact that each of these designs has well-known shortcomings: cross-sectional designs confound developmental differences with generation (cohort) differences; and longitudinal designs confound developmental differences with time-of-measurement differences. A theoretically preferable approach is the mixed-longitudinal design, but little experience with the data analytic aspects of such studies has been accumulated. We develop strategies for the analysis of data collected in accordance with a mixed-longitudinal study design and illustrate their use on several anthropometric measurements taken as part of the Nymegen Growth Study. Mixed-longitudinal designs can be viewed as a convenient combination of the cross-sectional and longitudinal approaches and, when used in conjunction with appropriate analytic techniques, mixed-longitudinal designs represent at least a partial solution to the problems of confounding alluded to above.