Developmental processes unfold across timescales ranging from seconds to decades, yet temporal assumptions often elude direct theoretical scrutiny. This review illustrates that decisions about timescale, including how time is defined, the density and duration of observations, the temporal windows encoded in measures, and the role time plays in statistical models, are essential, substantive theoretical decisions that determine what kinds of change a study can detect and what inferences it can support. The review first examines what time represents in developmental research and how it can be operationalized, including clock time, process-based time, event-based time, and subjective time. It then considers how study design features encode temporal assumptions. Finally, it organizes statistical models around three roles time can play: predictor, outcome, and moderator. Throughout, the review emphasizes the necessity of synchronizing theoretical models, data acquisition plans, and statistical models around coherent temporal frameworks.
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Aidan G.C. Wright (2026) studied this question.
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