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Jason Schoeneberger; Christopher Rhoads – Grantee Submission, 2024
Regression discontinuity (RD) designs are increasingly used for causal evaluations. For example, if a student's need for a literacy intervention is determined by a low score on a past performance indicator and that intervention is provided to all students who fall below a cutoff on that indicator, an RD study can determine the intervention's main…
Descriptors: Regression (Statistics), Causal Models, Evaluation Methods, Multivariate Analysis
Jason A. Schoeneberger; Christopher Rhoads – American Journal of Evaluation, 2025
Regression discontinuity (RD) designs are increasingly used for causal evaluations. However, the literature contains little guidance for conducting a moderation analysis within an RDD context. The current article focuses on moderation with a single binary variable. A simulation study compares: (1) different bandwidth selectors and (2) local…
Descriptors: Regression (Statistics), Causal Models, Evaluation Methods, Multivariate Analysis
Chuenjai Sukpan; Rebecca M. Kuiper – Structural Equation Modeling: A Multidisciplinary Journal, 2024
The (Random Intercept) Cross-Lagged Panel Model ((RI-)CLPM) is increasingly used in psychology and related fields to assess the longitudinal relationship of two or more variables on each other. Researchers are interested in the question which of the lagged effects is causally dominant receives considerable attention. However, currently used…
Descriptors: Causal Models, Psychological Studies, Multivariate Analysis, Cognitive Mapping
Alexander Robitzsch; Oliver Lüdtke – Structural Equation Modeling: A Multidisciplinary Journal, 2025
The random intercept cross-lagged panel model (RICLPM) decomposes longitudinal associations between two processes X and Y into stable between-person associations and temporal within-person changes. In a recent study, Bailey et al. demonstrated through a simulation study that the between-person variance components in the RICLPM can occur only due…
Descriptors: Longitudinal Studies, Correlation, Time, Simulation
Philip Haynes; David Alemna – International Journal of Social Research Methodology, 2024
Three quantitative methods are compared for their ability to understand different COVID-19 fatality ratios in 33 OECD countries. Linear regression provides a limited overview without sensitivity to the diversity of cases. Cluster Analysis and Dynamic Patterns Synthesis (DPS) gives scrutiny to the granularity of case similarities and differences,…
Descriptors: COVID-19, Regression (Statistics), Diversity, Multivariate Analysis
Ting Ye; Ted Westling; Lindsay Page; Luke Keele – Grantee Submission, 2024
The clustered observational study (COS) design is the observational study counterpart to the clustered randomized trial. In a COS, a treatment is assigned to intact groups, and all units within the group are exposed to the treatment. However, the treatment is non-randomly assigned. COSs are common in both education and health services research. In…
Descriptors: Nonparametric Statistics, Identification, Causal Models, Multivariate Analysis
Minjung Kim; Christa Winkler; James Uanhoro; Joshua Peri; John Lochman – Structural Equation Modeling: A Multidisciplinary Journal, 2022
Cluster memberships associated with the mediation effect are often changed due to the temporal distance between the cause-and-effect variables in longitudinal data. Nevertheless, current practices in multilevel mediation analysis mostly assume a purely hierarchical data structure. A Monte Carlo simulation study is conducted to examine the…
Descriptors: Hierarchical Linear Modeling, Mediation Theory, Multivariate Analysis, Causal Models
Bartolucci, Francesco; Pennoni, Fulvia; Vittadini, Giorgio – Journal of Educational and Behavioral Statistics, 2023
In order to evaluate the effect of a policy or treatment with pre- and post-treatment outcomes, we propose an approach based on a transition model, which may be applied with multivariate outcomes and accounts for unobserved heterogeneity. This model is based on potential versions of discrete latent variables representing the individual…
Descriptors: Causal Models, Multivariate Analysis, Markov Processes, Human Capital
Soenens, Bart; Berzonsky, Michael D.; Papini, Dennis R. – International Journal of Behavioral Development, 2016
Although research suggests an interplay between identity development and self-esteem, most studies focused on the role of identity commitment and measured only level of self-esteem. This study examined longitudinal associations between Berzonsky's (2011) styles of identity exploration and two distinct features of self-esteem: level of self-esteem…
Descriptors: Self Esteem, Individual Development, Longitudinal Studies, Questionnaires
Erdener, Mehmet Akif – Universal Journal of Educational Research, 2016
Parent involvement has an influence on children's educational engagement for all school levels. The objective of this study was to examine public school principals' and teachers' practices for improving parent involvement in schooling. This study used a mixed method to identify the school administrators' and teachers' perceptions about parent…
Descriptors: Principals, Parent Participation, Foreign Countries, Mixed Methods Research