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This article reviews the current status of methods available for the analysis of psychological change in adulthood and aging. Enormous progress has been made in designing statistical models that can capture key aspects of intraindividual change, as reflected in techniques such as latent growth curve models and multilevel (random-effects) models. However, the rapid evolution of statistical innovations may have obscured the critical importance of addressing rival explanations for statistical outcomes, such as cohort differences or practice effects that could influence estimates of age-related change. Choice of modeling technique and implementation of a specific modeling approach should be grounded in and reflect both the theoretical nature of the developmental phenomenon and the features of the sampling design that selected persons, variables, and contexts for empirical observation.
Hertzog et al. (2003) studied this question.