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…

This article is concerned with the assumption of linear temporal development that is often advanced in structural equation modeling-based longitudinal research. The linearity hypothesis is implemented in particular in the popular intercept-and-slope model as well as in more general models containing it as a component, such as longitudinal…

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.…

The social relations model (SRM) is very often used in psychology to examine the components, determinants, and consequences of interpersonal judgments and behaviors that arise in social groups. The standard SRM was developed to analyze cross-sectional data. Based on a recently suggested integration of the SRM with structural equation models (SEM)…

Dynamic structural equation modeling (DSEM) is a useful technique for analyzing intensive longitudinal data. A challenge of applying DSEM is the missing data problem. The impact of missing data on DSEM, especially on widely applied DSEM such as the two-level vector autoregressive (VAR) cross-lagged models, however, is understudied. To fill the…

Dynamic structural equation modeling (DSEM) is a useful technique for analyzing intensive longitudinal data. A challenge of applying DSEM is the missing data problem. The impact of missing data on DSEM, especially on widely applied DSEM such as the two-level vector autoregressive (VAR) cross-lagged models, however, is understudied. To fill the…

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…

Accelerated longitudinal designs (ALDs) provide an opportunity to capture long developmental periods in a shorter time framework using a relatively small number of assessments. Prior literature has investigated whether univariate developmental processes can be characterized with data obtained from ALDs. However, many important questions in…

Structural equation modeling and autoethnography have rarely been integrated in scientific studies. The example employs a convergent intensive longitudinal data collection strategy and an explanatory bidirectional framework for data merging analysis to examine one instructor's practices of incorporating social-emotional learning (SEL) and…

As colleges and universities grapple with uncertainty around current and future enrollment as well as increasingly vocal questions about the value of postsecondary education, it is critically important that institutions ascertain and invest in the elements of campus learning and engagement that add value to the undergraduate experience. This study…

The Stranger Face Trust scale (SFT) and Imaginary Stranger Trust scale (IST) are two new self-report measures of generalized trust that assess trust in strangers--both real and imaginary--across four trust domains. Prior research has established the reliability and validity of SFT and IST, but a number of measurement validation tests remain.…

Measuring change in an educational or psychological construct over time is often achieved by repeatedly administering the same items to the same examinees over time and fitting a second-order latent growth curve model. However, latent growth modeling with full information maximum likelihood (FIML) estimation becomes computationally challenging…

Organic chemistry presents a significant obstacle for students seeking entry into health-related professions. Students' ability to develop effective study approaches is an important predictor of success in the course. Herein, we report an investigation utilizing an OCH-adjusted M-ASSIST instrument to assess possible changes in students' study…

To examine developmental processes, intervention effects, or both, longitudinal studies often aim to include measurement intervals that are equally spaced for all participants. In reality, however, this goal is hardly ever met. Although different approaches have been proposed to deal with this issue, few studies have investigated the potential…

The important role of early self-regulation skills has been repeatedly demonstrated in research. However, there is a lack of studies that have simultaneously examined the influence of hot and cool self-regulation skills on school performance and behavior problems in a longitudinal design from preschool to elementary school and controlling…