Characterization of developmental trajectories across the lifespan is integral to understanding the prodromal course of many neuropsychiatric illnesses and the significant risk factors for disease onset or unfavorable outcomes. However, the standard experimental designs used in psychiatric research are not ideal for this purpose. The authors review the limitations of the most commonly employed designs in studies that make developmental or lifespan inferences in psychiatry: cross-sectional, single-cohort longitudinal, and unstructured multicohort longitudinal designs. Cross-sectional studies completely confound within- and between-subject sources of variation and hence rely on the presence of parallel trajectories and negligible sampling and age cohort differences for making valid developmental inferences. Delineating trajectories of within-individual change over substantial periods of time requires data covering long age spans that often cannot be covered using single-cohort longitudinal designs. Unstructured multicohort longitudinal designs are a commonly used alternative that can cover a longer age span in a shorter interval than necessary for a single-cohort design. However, the impact of cohort and sampling effects is often minimized or ignored in unstructured multicohort longitudinal designs. The authors propose that structured multicohort longitudinal designs are a particularly viable and underutilized class of designs in psychiatry that represents a significant improvement over cross-sectional designs and unstructured multicohort longitudinal designs for making developmental inferences while being more practical to implement than single-cohort longitudinal designs. As an example of this approach, the authors analyze changes in entorhinal cortex thickness in Alzheimer's disease in relation to APOE-ε4 genotype.