One major challenge of longitudinal data analysis is to find an appropriate statistical model that corresponds to the theory of change and the research questions at hand. In the present article, we argue that "continuous-time models" are well suited to study the continuously developing constructs of primary interest in the education…

The aim of this study is to validate an instrument to evaluate the teaching of mathematics through mathematical processes using a structural equation model. To that end, we have administered the instrument to 95 in-service Spanish teachers and we have also analysed the presence of mathematical processes (problem solving, reasoning and proof,…

Purpose: The purpose of this paper is to conduct a critical review of the mediation studies published in the field of Human Resource Development (HRD) to discern if the study designs, the nature of data collection and the choice of statistical methods justify the causal claims made in those studies. Design/methodology/approach: This paper conducts…

Growth mixture modeling (GMM) has become a more popular statistical method for modeling population heterogeneity in longitudinal data, but the performance characteristics of GMM enumeration indexes in correctly identifying heterogeneous growth trajectories are largely unknown. Few empirical studies have addressed this issue. This study considered…

This study examines the changes in educational inequality at the school- and individual-levels in 1991 and 2001. Comparisons are made between the IEA Reading Literacy Study 1991 and the so called 10-Year Trend Study in PIRLS 2001. The between-school differences in reading achievement variance and the size of the relationship between SES and…

This article uses a general latent variable framework to study a series of models for nonignorable missingness due to dropout. Nonignorable missing data modeling acknowledges that missingness may depend not only on covariates and observed outcomes at previous time points as with the standard missing at random assumption, but also on latent…

This article investigates three types of stage-sequential growth mixture models in the structural equation modeling framework for the analysis of multiple-phase longitudinal data. These models can be important tools for situations in which a single-phase growth mixture model produces distorted results and can allow researchers to better understand…

Does adolescent depressed mood portend increased or decreased drinking? Is frequent drinking positively or negatively associated with emotional well-being? Do the dynamic relations between depression and drinking differ by gender? Using block-recursive structural equation models, we explore the reciprocal short-term effects (within time, "t") and…

Latent growth curve modeling provides a powerful and flexible tool for researchers to study individual differences in change as well as the correlates and predictors of change. Recent developments in estimation and hypothesis testing procedures are largely based on confirmatory structural equation approaches. In this article, an alternative…