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Martin Sliwinski & Jacqueline Mogle

In: Handbook of Cognitive Aging: Interdisciplinary Perspectives

Chapter 28: Time-Based and Process-Based Approaches to Analysis of Longitudinal Data

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Time-Based and Process-Based Approaches to Analysis of Longitudinal Data
Time-based and process-based approaches to analysis of longitudinal data

The science of aging seeks to explain why individuals lose, gain, or maintain functioning in different domains (e.g., cognition, health, and emotion) as they transition from young adulthood through middle and into old age (Baltes, Staudinger, & Lindenberger, 1999; Wohlwill, 1973). Although aging research is concerned with how individuals change across the adult life span, aging theories are primarily informed by cross-sectional comparisons of how individuals differ as a function of their age. Average cross-sectional age differences may approximate the magnitude, on average, of longitudinal age change; however, cross-sectional data cannot unambiguously disentangle effects caused by aging versus stable individual-differences characteristics. Longitudinal data provide a unique opportunity to ...

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