Age, cohort, and time development muddles: easy in practice, hard in theory

Area of Science:

• Psychology
• Sociology
• Statistics

Background:

• The combination of longitudinal and cross-sectional data in developmental psychology presents persistent challenges.
• Decades of debate exist on effectively integrating these data types to understand developmental influences.
• Previous discussions have been limited by a narrow focus and obscured formal indeterminacy.

Purpose of the Study:

• To address the long-standing debate in developmental psychology regarding the integration of longitudinal and cross-sectional data.
• To clarify the complexities of disentangling age, cohort, and time effects in developmental research.
• To introduce and review interdisciplinary contributions that offer solutions to these methodological challenges.

Main Methods:

• Review of methodological and substantive contributions from psychology, sociology, and statistics.
• Analysis of formal solutions for model identification and estimability in developmental models.
• Examination of theoretically based solutions for unambiguous interpretation of age, cohort, and time parameters.

Main Results:

• Developmental psychologists have largely overlooked valuable insights from other disciplines.
• Existing approaches often obscure the inherent indeterminacy in models of age, cohort, and time.
• Formal solutions from methodologists and theoretical assumptions from sociologists offer pathways to resolve indeterminacy.

Conclusions:

• A more integrated, interdisciplinary approach is needed to effectively combine developmental data sequences.
• Explicit theoretical assumptions are crucial for model identification and unambiguous interpretation.
• A hierarchy of solutions is proposed to address the age, cohort, and time indeterminacy problem in developmental psychology.