During the past two decades, methods for identifying groups with different trends in
longitudinal data have become of increasing interest across many areas of research. To …

Abstract Three-dimensional (3D) surfaces of wear particles were reconstructed through multi-
view contour fitting and dense point-cloud interpolation with an aim to obtain comprehensive …

In this article, we propose a nonlinear dynamic latent class structural equation modeling
(NDLC-SEM). It can be used to examine intra-individual processes of observed or latent …

Multilevel and latent growth modeling analysis (GMA) is often used to compare independent
groups in linear random slopes of outcomes over time, particularly in randomized controlled …

During the past two decades, methods for identifying groups with different trends in
longitudinal data have become of increasing interest across many areas of research. To …

Growth mixture models combine latent growth curve models and finite mixture models to
examine the existence of latent classes that follow distinct developmental patterns. Analyses …

Longitudinal data analysis has received widespread interest throughout educational,
behavioral, and social science research, with latent growth curve modeling currently being …

The effect of an independent variable on random slopes in growth modeling with latent
variables is conventionally used to examine predictors of change over the course of a study …

A novel algorithmic modeling method is proposed to determine dissimilarities between
subjects for longitudinal data clustering using natural cubic smoothing splines. Although …

The difference between groups in their random slopes is frequently examined in latent
growth modeling to evaluate treatment efficacy. However, when end centering is used for …