This study aims to estimate the latent interaction effect in the CLPM model through a two-step multiple imputation analysis. The estimation of within x within and between x within latent interaction under the CLPM model framework is compared between the one-step Bayesian LMS method and the two-step multiple imputation analysis through a simulation…

Longitudinal research is often interested in identifying correlates of heterogeneity in change. This paper compares three approaches for doing so: the mixed-effects model (latent growth curve model), the growth mixture model, and structural equation model trees. Each method is described, with special focus given to how each structures…

Context: Prolonged disconnection from school and work represents major setbacks during the transition to adulthood and is a distinct feature of the developmental trajectories of many disadvantaged youths, especially those from a marginalized racial background (Hong and Chung 2022; Shanahan 2000). Differential schooling experiences are hypothesized…

The impact of a major historical event on child and youth development has been of great interest in the study of the life course. This study is focused on assessing the causal effect of the Great Recession on youth disconnection from school and work. Building on the insights offered by the age-period-cohort research, econometric methods, and…

As young people progress with their education and their early careers, they find themselves pushed forward or held back at critical junctures without full regard for their individual capabilities. Their paths are too often defined less by their talents and more by characteristics such as their race/ethnicity, gender, and socioeconomic or class…

Growth mixture models (GMMs) are prevalent for modeling unknown population heterogeneity via distinct latent classes. However, GMMs are riddled with convergence issues, often requiring researchers to atheoretically alter the model with cross-class constraints to obtain convergence. We discuss how within-class random effects in GMMs exacerbate…

Despite broad applications of growth curve models, few studies have dealt with a practical issue -- nonnormality of data. Previous studies have used Student's "t" distributions to remedy the nonnormal problems. In this study, robust distributional growth curve models are proposed from a semiparametric Bayesian perspective, in which…

Misclassification means the observed category is different from the underlying one and it is a form of measurement error in categorical data. The measurement error in continuous, especially normally distributed, data is well known and studied in the literature. But the misclassification in a binary outcome variable has not yet drawn much attention…

Existing empirical work looking at the effects of parental income on IQ, schooling, wealth, race, and personality is only able to explain about half of the observed intergenerational income elasticity. This paper provides a possible behavioral explanation for this elasticity in which heterogeneous agents in sequential generations choose their…

The purpose of this study was to investigate the mediation effects of children's cognitive and noncognitive traits on the relationship between dropout mothers' traits and their children's educational expectations and to examine the interaction effects of dropout mothers' General Education Development (GED) on children's traits and educational…

This article provides family scientists with an understanding of contemporary measurement perspectives and the ways in which item response theory (IRT) can be used to develop measures with desired evidence of precision and validity for research uses. The article offers a nontechnical introduction to some key features of IRT, including its…

Few studies have examined the relation between maternal caloric intake during pregnancy and growth in child academic achievement while controlling for important confounding influences. Using data from the National Longitudinal Survey of Youth, the current study examined the effects of reduced prenatal caloric intake on growth in scores on the…

Often in sociology, researchers are confronted with nonnormal variables whose joint distribution they wish to explore. Yet, assumptions of common measures of dependence can fail or estimating such dependence is computationally intensive. This article presents the copula method for modeling the joint distribution of two random variables, including…

This study examined achievement trajectories in mathematics and reading from school entry through the end of middle school with linear and nonlinear growth curves in 2 large longitudinal data sets (National Longitudinal Study of Youth--Children and Young Adults and Early Childhood Longitudinal Study--Kindergarten Cohort [ECLS-K]). The S-shaped…

Latent difference score (LDS) models combine benefits derived from autoregressive and latent growth curve models allowing for time-dependent influences and systematic change. The specification and descriptions of LDS models include an initial level of ability or trait plus an accumulation of changes. A limitation of this specification is that the…