Extending Latent Basis Growth Model to Explore Joint Development in the Framework of Individual Measurement Occasions

Abstract

Longitudinal processes often exhibit nonlinear change patterns. Latent basis growth models (LBGMs) provide a versatile solution without requiring specific functional forms. Building on the LBGM specification for unequally-spaced waves and individual measurement occasions proposed by Liu and Perera (2023), we extend LBGMs to multivariate longitudinal outcomes. The extended models enable the analysis of nonlinear parallel longitudinal processes with unequally-spaced study waves in the framework of individual measurement occasions. We present the proposed models by simulation studies and real-world data analyses. Simulation studies demonstrate that the proposed model can provide unbiased and accurate estimates with target coverage probabilities for the parameters of interest. Real-world analyses of reading and mathematics scores demonstrate its effectiveness in analyzing joint developmental processes that vary in temporal patterns. Computational code is included.