Abstract
Longitudinal planned missing, represented in the literature by the time-lag model (McArdle&Woodcock, 1997) and the cohort sequential design (Nesselroade&Baltes, 1979), has been thus far restricted to growth modeling and often does not fully utilize the benefits of the planned missingness by estimating a full-longitudinal model. The accelerated longitudinal design may serve as a more flexible and powerful alternative. This study presents a test of the accelerated longitudinal design in a simulated latent panel modeling framework to examine the method's appropriateness for contexts untestable using traditional longitudinal planned missing designs. Three-, four-, and five-cohort models are tested, using a continuum of sample sizes and cohort effect sizes. Results indicate that factor loadings, factor variances, and stabilities across time are replicated well, while characteristics and relationships of the means (i.e., manifest intercepts, latent means, and especially cohort differences) show low efficiency relative to the full sample case. In general, the technique is recommended when no cohort effects are expected, though more expansive research into other possible modeling situations should follow.