Modeling life-span growth curves of cognition using longitudinal data with multiple samples and changing scales of measurement

Abstract

The authors use multiple-sample longitudinal data from different test batteries to examine propositions about changes in constructs over the life span. The data come from 3 classic studies on intellectual abilities in which, in combination, 441 persons were repeatedly measured as many as 16 times over 70 years. They measured cognitive constructs of vocabulary and memory using 8 age-appropriate intelligence test batteries and explore possible linkage of these scales using item response theory (IRT). They simultaneously estimated the parameters of both IRT and latent curve models based on a joint model likelihood approach (i.e., NLMIXED and WINBUGS). They included group differences in the model to examine potential interindividual differences in levels and change. The resulting longitudinal invariant Rasch test analyses lead to a few new methodological suggestions for dealing with repeated constructs based on changing measurements in developmental studies.

Figure 1

Growth curves of intellectual abilities from the Berkeley Growth Studies of Bayley (1956; Age 16 D scores).

Figure 2

Longitudinal plots of Rasch estimated person abilities against age for (A) Vocabulary and (B) Memory abilities.

Figure 3

Latent Growth Curve Model expected group trajectories based on the dual exponential model with one standard deviation around the mean for (A) Vocabulary and (B) Memory abilities.

Figure 4

Expected group growth curves of (A) Vocabulary and (B) Memory abilities for the three independent study groups – the Berkeley Growth Study (BGS), the Guidance Control Study (GCS), and the Bradway-McArdle Longitudinal Study (BML).