Marsh (1998; also see Baltes & Nesselroade, 1979) argued that multicohort-multioccasion designs provide a stronger basis for assessing developmental self-concept differences than a typical cross-sectional methodology (comparisons of different age cohorts collected on a single occasion) or a true longitudinal methodology (comparisons of responses by a single age cohort collected on multiple occasions). In particular, the juxtaposition of the age effects based on the (cross-sectional) age cohort and the true longitudinal comparisons based on multiple occasions within each age cohort provide an important multimethod approach to cross-validating interpretations based on these two alternative methods of evaluating developmental trends. Marsh, Craven, and Debus (1998) used a multicohort-multioccasion design with two waves of data collected 1 year apart with the same children in each of three age cohorts. The contrast between cross-sectional and true longitudinal comparisons provided a much stronger basis for evaluating age-related differences in reliability, stability over time,'dimensionality, and gender differences.
In another application of this approach, Marsh (1998) evaluated age and gender effects in 10 physical self-concept scales for elite athletes and nonath-letes, based on responses from four high-school-age cohorts who each completed the same instrument four times during a 2-year period. Across all 10 physical self-concepts there were substantial differences because of group (athletes > nonathletes), gender (males > females), and gender X group interactions (gender differences smaller for athletes than nonathletes). There were no significant effects of age cohort (year in school) and only very small effects of occasions. Thus longitudinal and cross-sectional comparisons were in agreement showing that mean levels of physical self-concept were stable over this potentially volatile adolescent period and that this stability generalized over gender, age, and the athlete groups. Wen, Marsh, and Hau (2003)
extended the analysis of this data to incorporate a growth modeling approach that provided many advantages in assessing individual patterns of growth as well as mean differences averaged across all individuals within a cohort (e.g., age cohorts) or groups (e.g., gender or athletic groups).
Anticipating subsequent emphases on latent growth modeling and the analysis of mean structures, Marsh and Grayson (1994b) developed procedures to evaluate invariance of mean structures at the item level over time. Based on five waves of data collected over an 8-year period, they showed that their approach was more flexible than the traditional repeated measures approach. They also found, however, a potential lack of invariance at the item intercept level over time, suggesting that the meaning of some items may have changed over this early-adolescent to late-adolescent period and posing a threat to the interpretation of self-concept latent means over time. Based on these results they proposed a hierarchy of invariances and what substantive interpretations were justified at different levels of invariance. Although their focus was on longitudinal data, it could easily be extended to a multicohort-multioccasion design that combined cross-sectional and longitudinal approaches. This combined approach could address, for example, the issue of whether noninvariance in item intercepts reflected a developmental shift in the interpretations of the items or cohort differences in the way adolescents interpret item wording.
Studies summarized in this section demonstrate the usefulness of the multicohort-multioccasion design for cross-validating interpretations based on cross-sectional and longitudinal methodologies. It is important to emphasize, however, that this type of multimethod data opens up rich possibilities for evaluating a wide range of substantive developmental issues using a variety of analytic techniques (e.g., Bijleveld & van der Kamp, 1998; Little, Schnabel, & Baumert, 2000).
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