This study proposes a two-stage causal modeling with instrumental variables to mitigate selection bias, provide correct standard error estimates, and address nonnormal and missing data issues simultaneously. Bayesian methods are used for model estimation. Robust methods with Student's "t" distributions are used to account for nonnormal…

This manual provides guidance and documentation for users of the kindergarten (or base year) data of the Early Childhood Longitudinal Study, Kindergarten Class of 2010-11 (ECLS-K:2011). It begins with an overview of the ECLS-K:2011. Subsequent chapters provide details on the study data collection instruments and methods; the direct and indirect…

This manual provides guidance and documentation for users of the longitudinal kindergarten-first grade (K-1) data file of the Early Childhood Longitudinal Study, Kindergarten Class of 2010-11 (ECLS-K:2011). It mainly provides information specific to the first-grade rounds of data collection. Data for the ECLS-K:2011 are released in both a…

Growth mixture models (GMMs; B. O. Muthen & Muthen, 2000; B. O. Muthen & Shedden, 1999) are a combination of latent curve models (LCMs) and finite mixture models to examine the existence of latent classes that follow distinct developmental patterns. GMMs are often fit with linear, latent basis, multiphase, or polynomial change models…