Latent growth models (LGMs) are an application of structural equation modeling and frequently used in developmental and clinical research to analyze change over time in longitudinal outcomes. Maximum likelihood (ML), the most common approach for estimating LGMs, can fail to converge or may produce biased estimates in complex LGMs especially in…

Piecewise GMM with unknown turning points is a new procedure to investigate heterogeneous subpopulations' growth trajectories consisting of distinct developmental phases. Unlike the conventional PGMM, which relies on theory or experiment design to specify turning points a priori, the new procedure allows for an optimal location of turning points…

Few issues in education threaten the nation as seriously as the present and growing shortage of teachers. Teacher attrition is high among teachers across the nation and is one of the most serious causes of teacher shortage (Ingersoll, 2004). As policy makers rush to address this problem, research is needed to examine the retention effects of…

This study examined the extent to which socioemotional well-being mediated the relationship between language status and achievement, while exploring variability in this relationship based on informant (student versus teacher reports of socioemotional problems) and native language background (Spanish-speaking English language learners [ELLs] versus…

Maximum likelihood estimation of mixed effect baseline category logit models for multinomial longitudinal data can be prohibitive due to the integral dimension of the random effects distribution. We propose to use multidimensional unfolding methodology to reduce the dimensionality of the problem. As a by-product, readily interpretable graphical…

Students with significant cognitive disabilities are eligible to participate in two statewide testing options for accountability: alternate assessments or general assessments with appropriate accommodations. Participation guidelines are generally quite vague, leading to students "switching" test participation between years. In this…

In this study, we examine the development of student engagement in relation to dropout. We focus on different growth trajectories of engagement between groups of students and on whether these trajectories lead to differences in the survival of the student. The development of behavioural and emotional engagement of 4063 graduates and 541 (11.7%)…

This longitudinal study investigated the contribution of achievement goals and academic self-concept for the prediction of unexpected academic achievement (i.e., achievement that is higher or lower than expected with respect to students' cognitive ability) in general and when comparing groups of extreme over- and underachievers. Our sample…

Maximum likelihood (ML) estimation of generalized linear mixed models (GLMMs) is technically challenging because of the intractable likelihoods that involve high dimensional integrations over random effects. The problem is magnified when the random effects have a crossed design and thus the data cannot be reduced to small independent clusters. A…

The capacity of Bayesian methods in estimating complex statistical models is undeniable. Bayesian data analysis is seen as having a range of advantages, such as an intuitive probabilistic interpretation of the parameters of interest, the efficient incorporation of prior information to empirical data analysis, model averaging and model selection.…

Presents an application of latent growth curve methodology to the analysis of longitudinal developmental change in alcohol consumption of 586 young adults, illustrating three approaches to the analysis of missing data: (1) multiple-sample structural equation modeling procedures; (2) raw maximum likelihood analyses; and (3) multiple modeling and…