Tests for linkage of multiple cohorts in an accelerated longitudinal design

In accelerated longitudinal design, one samples multiple age cohorts and then collects longitudinal data on members of each cohort. The aim is to study age-outcome trajectories over a broad age span during a study of short duration. A threat to valid inference is the Age x Cohort interaction effect. S. W. Raudenbush and W. S. Chan (1993) developed a test for such interactions in the context of 2 cohorts by using a hierarchical model. The current article extends this approach to include any number of cohorts. Using the National Youth Survey, the authors combine data collected on 7 cohorts over 5 years to approximate change in antisocial attitudes between 11 and 21 years of age. They show how to test for cohort differences in trajectories, how to calculate the power of the test, and how to use graphical procedures to aid understanding. The approach allows unbalanced designs and the clustering of participants within families, neighborhoods, or other social units.