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Steffen Nestler; Sarah Humberg – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Several variants of the autoregressive structural equation model were suggested over the past years, including, for example, the random intercept autoregressive panel model, the latent curve model with structured residuals, and the STARTS model. The present work shows how to place these models into a mixed-effects model framework and how to…
Descriptors: Structural Equation Models, Computer Software, Models, Measurement
Tomek, Sara; Robinson, Cecil – Measurement: Interdisciplinary Research and Perspectives, 2021
Typical longitudinal growth models assume constant functional growth over time. However, there are often conditions where trajectories may not be constant over time. For example, trajectories of psychological behaviors may vary based on a participant's age, or conversely, participants may experience an intervention that causes trajectories to…
Descriptors: Growth Models, Statistical Analysis, Hierarchical Linear Modeling, Computation
Craig K. Enders – Grantee Submission, 2023
The year 2022 is the 20th anniversary of Joseph Schafer and John Graham's paper titled "Missing data: Our view of the state of the art," currently the most highly cited paper in the history of "Psychological Methods." Much has changed since 2002, as missing data methodologies have continually evolved and improved; the range of…
Descriptors: Data, Research, Theories, Regression (Statistics)
Koster, Jeremy; Leckie, George; Aven, Brandy – Field Methods, 2020
The multilevel social relations model (SRM) is a commonly used statistical method for the analysis of social networks. In this article and accompanying supplemental materials, we demonstrate the estimation and interpretation of the SRM using Stat-JR software. Multiple software templates permit the analysis of different response types, including…
Descriptors: Statistical Analysis, Computer Software, Hierarchical Linear Modeling, Social Networks
Rindskopf, David; Shadish, William; Hedges, Larry V. – Online Submission, 2012
This conference presentation demonstrates a multilevel model for analyzing single case designs. The model is implemented in the Bayesian program WinBUGS. The authors show how it is possible to estimate a d-statistic like the one in Hedges, Pustejovsky and Shadish (2012) in this program. Results are demonstrated on an example.
Descriptors: Effect Size, Computation, Hierarchical Linear Modeling, Research Design
Hedges, Larry V.; Hedberg, E. C.; Kuyper, Arend M. – Educational and Psychological Measurement, 2012
Intraclass correlations are used to summarize the variance decomposition in populations with multilevel hierarchical structure. There has recently been considerable interest in estimating intraclass correlations from surveys or designed experiments to provide design parameters for planning future large-scale randomized experiments. The large…
Descriptors: Correlation, Computation, Hierarchical Linear Modeling, Reading Achievement