NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 6 results Save | Export
Creative Self-Efficacy and Personality: From Imagination to Creativity
Peer reviewed Peer reviewed
Direct linkDirect link
Lamb, Kristen; Kettler, Todd – AERA Online Paper Repository, 2019
Imagination and creative self-efficacy (CSE) are important components of the creative process and outcomes but are rarely investigated together. To explore the relationship between personality factors, imaginative thinking, and CSE, survey responses were gathered from university students in a southwestern region in the United States (n = 1,731).…
Descriptors: Creativity, Self Efficacy, Personality Traits, Imagination
Statistical Power of the Multiple-Domain Latent Growth Model for Detecting Group Differences
Peer reviewed Peer reviewed
Direct linkDirect link
Lee, Kejin; Whittaker, Tiffany Ann – AERA Online Paper Repository, 2017
The latent growth model (LGM) in structural equation modeling (SEM) may be extended to allow for the modeling of associations among multiple latent growth trajectories, resulting in a multiple domain latent growth model (MDLGM). While the MDLGM is conceived as a more powerful multivariate analysis technique, the examination of its methodological…
Descriptors: Statistical Analysis, Growth Models, Structural Equation Models, Multivariate Analysis
The Impact of Prior Specifications on Model Comparison in Bayesian Structural Equation Modeling
Peer reviewed Peer reviewed
Direct linkDirect link
Huang, Jiajing; Liang, Xinya; Yang, Yanyun – AERA Online Paper Repository, 2017
In Bayesian structural equation modeling (BSEM), prior settings may affect model fit, parameter estimation, and model comparison. This simulation study was to investigate how the priors impact evaluation of relative fit across competing models. The design factors for data generation included sample sizes, factor structures, data distributions, and…
Descriptors: Bayesian Statistics, Structural Equation Models, Goodness of Fit, Sample Size
A Comparison of Multilevel Mediation Modeling Methods
Peer reviewed Peer reviewed
Direct linkDirect link
Zigler, Christina K.; Ye, Feifei – AERA Online Paper Repository, 2016
Mediation in multi-level data can be examined using conflated multilevel modeling (CMM), unconflated multilevel modeling (UMM), or multilevel structural equation modeling (MSEM). A Monte Carlo study was performed to compare the three methods on bias, type I error, and power in a 1-1-1 model with random slopes. The three methods showed no…
Descriptors: Hierarchical Linear Modeling, Structural Equation Models, Monte Carlo Methods, Statistical Bias
Factors Affecting the Robust Weighted Least Squares Model Fit Measures in Confirmatory Factor Analysis
Peer reviewed Peer reviewed
Direct linkDirect link
Zhao, Yu; Lei, Pui-Wa – AERA Online Paper Repository, 2016
Despite the prevalence of ordinal observed variables in applied structural equation modeling (SEM) research, limited attention has been given to model evaluation methods suitable for ordinal variables, thus providing practitioners in the field with few guidelines to follow. This study represents a first attempt to thoroughly examine the…
Descriptors: Factor Analysis, Monte Carlo Methods, Causal Models, Least Squares Statistics
Examining Student and Home Factors Leading to Successful Chinese Reading in the International PIRLS (Progress in International Reading Literacy Study) 2011
Peer reviewed Peer reviewed
Direct linkDirect link
Cheung, Wai Ming; Huang, Yanli; Tsang, Hector W. H. – AERA Online Paper Repository, 2017
Hong Kong attained champion of the PIRLS 2011 that aroused keen interest in understanding the underlying reasons of a non-alphabetic language. The study aimed at unravelling various aspects of the student and home factors which contributed to remarkable Chinese reading performance. Totally 3,875 students from 132 primary schools completed the…
Descriptors: Chinese, Reading Achievement, Elementary School Students, Structural Equation Models