Intensive longitudinal data has been widely used to examine reciprocal or causal relations between variables. However, these variables may not be temporally aligned. This study examined the consequences and solutions of the problem of temporal misalignment in intensive longitudinal data based on dynamic structural equation models. First the impact…

Studying development processes, as they unfold over time, involves collecting repeated measures from individuals and modeling the changes over time. One methodological challenge in this type of longitudinal data is separating retest effects, due to the repeated assessments, from developmental processes such as maturation or age. In this article,…

This study simplifies the seven different cross-lagged panel models (CLPMs) by using the RSEM model for both inter-individual and intra-individual structures. In addition, the study incorporates the newly developed dynamic panel model (DPM), general cross-lagged model (GCLM) and the random intercept auto-regressive moving average (RI-ARMA) model.…

Diagnostic classification models (DCMs) have grown in popularity as stakeholders increasingly desire actionable information related to students' skill competencies. Longitudinal DCMs offer a psychometric framework for providing estimates of students' proficiency status transitions over time. For both cross-sectional and longitudinal DCMs, it is…

Longitudinal data analysis has been widely employed to examine between-individual differences in within-individual changes. One challenge of such analyses is that the rate-of-change is only available indirectly when change patterns are nonlinear with respect to time. Latent change score models (LCSMs), which can be employed to investigate the…

Existing research on "school effectiveness" indicates that differences at the school level contribute significantly towards variation in student outcomes; however, less is known about the effectiveness of schooling in low- and middle-income countries (LMICs). This paper addresses this gap using quantitative analysis of data from two…

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…

The detection of differential item functioning (DIF) is important in psychological and behavioral sciences. Standard DIF detection methods perform an item-by-item test iteratively, often assuming that all items except the one under investigation are DIF-free. This article proposes a Bayesian adaptive Lasso method to detect DIF in graded response…

The present study compares two methods for assessing peer influence: the longitudinal actor-partner interdependence model (L-APIM) and the longitudinal social network analysis (L-SNA) Model. The data were drawn from 1,995 (49% girls and 51% boys) third grade students (M[subscript age] = 9.68 years). From this sample, L-APIM (n = 206…

Background: Over the past few decades early self-regulation has been identified as foundational to positive learning and wellbeing trajectories. As a consequence, a wide range of approaches have been developed to capture children's developmental progress in self-regulation. Little is known, however, about whether and which of these are reliable…

The purpose of this longitudinal study was to explore the development of pre-service chemistry teachers' pedagogical content knowledge regarding the effect of temperature on reaction rate topic as they took pedagogical content knowledge courses throughout the teacher education program. Pre-service teachers' pedagogical content knowledge was…

How have changes in the costs of enrolling for full-time study at public 2-year and 4-year colleges have affected the decisions about whether and where to enroll in college? We exploit local differences in the growth of tuition at community colleges and public 4-year colleges to study the impact of public higher education costs on the…

The recent popularity of models that capture the dynamic coevolution of both network structure and behavior has driven the need for summary indices to assess the adequacy of these models to reproduce dynamic properties of scientific or practical importance. Whereas there are several existing indices for assessing the ability of the model to…

Because the pandemic exacerbated chronic absenteeism in many parts of the country, the need to understand how schools can improve student attendance has never been greater. Accordingly, this study breaks new ground by examining high schools' contributions to attendance after accounting for individual students' prior absenteeism and other…

Several multivariate models are motivated to answer similar developmental questions regarding within-person (intraindividual) effects between 2 or more constructs over time, yet the within-person effects tested by each model are distinct. In this article, the authors clarify the types of within-person inferences that can be made from each model.…