NotesFAQContact Us
Collection
Advanced
Search Tips
Showing 1 to 15 of 23 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Raykov, Tenko; Calvocoressi, Lisa – Educational and Psychological Measurement, 2021
A procedure for evaluating the average R-squared index for a given set of observed variables in an exploratory factor analysis model is discussed. The method can be used as an effective aid in the process of model choice with respect to the number of factors underlying the interrelationships among studied measures. The approach is developed within…
Descriptors: Factor Analysis, Structural Equation Models, Statistical Analysis, Selection
Peer reviewed Peer reviewed
Direct linkDirect link
Sim, Mikyung; Kim, Su-Young; Suh, Youngsuk – Educational and Psychological Measurement, 2022
Mediation models have been widely used in many disciplines to better understand the underlying processes between independent and dependent variables. Despite their popularity and importance, the appropriate sample sizes for estimating those models are not well known. Although several approaches (such as Monte Carlo methods) exist, applied…
Descriptors: Sample Size, Statistical Analysis, Predictor Variables, Path Analysis
Peer reviewed Peer reviewed
Direct linkDirect link
Son, Sookyoung; Hong, Sehee – Educational and Psychological Measurement, 2021
The purpose of this two-part study is to evaluate methods for multiple group analysis when the comparison group is at the within level with multilevel data, using a multilevel factor mixture model (ML FMM) and a multilevel multiple-indicators multiple-causes (ML MIMIC) model. The performance of these methods was evaluated integrally by a series of…
Descriptors: Hierarchical Linear Modeling, Factor Analysis, Structural Equation Models, Groups
Peer reviewed Peer reviewed
Direct linkDirect link
Thompson, Yutian T.; Song, Hairong; Shi, Dexin; Liu, Zhengkui – Educational and Psychological Measurement, 2021
Conventional approaches for selecting a reference indicator (RI) could lead to misleading results in testing for measurement invariance (MI). Several newer quantitative methods have been available for more rigorous RI selection. However, it is still unknown how well these methods perform in terms of correctly identifying a truly invariant item to…
Descriptors: Measurement, Statistical Analysis, Selection, Comparative Analysis
Peer reviewed Peer reviewed
Direct linkDirect link
Hayes, Timothy; Usami, Satoshi – Educational and Psychological Measurement, 2020
Recently, quantitative researchers have shown increased interest in two-step factor score regression (FSR) approaches to structural model estimation. A particularly promising approach proposed by Croon involves first extracting factor scores for each latent factor in a larger model, then correcting the variance-covariance matrix of the factor…
Descriptors: Regression (Statistics), Structural Equation Models, Statistical Bias, Correlation
Peer reviewed Peer reviewed
Direct linkDirect link
Son, Sookyoung; Lee, Hyunjung; Jang, Yoona; Yang, Junyeong; Hong, Sehee – Educational and Psychological Measurement, 2019
The purpose of the present study is to compare nonnormal distributions (i.e., t, skew-normal, skew-t with equal skew and skew-t with unequal skew) in growth mixture models (GMMs) based on diverse conditions of a number of time points, sample sizes, and skewness for intercepts. To carry out this research, two simulation studies were conducted with…
Descriptors: Statistical Distributions, Statistical Analysis, Structural Equation Models, Comparative Analysis
Peer reviewed Peer reviewed
Direct linkDirect link
Paek, Insu; Cui, Mengyao; Öztürk Gübes, Nese; Yang, Yanyun – Educational and Psychological Measurement, 2018
The purpose of this article is twofold. The first is to provide evaluative information on the recovery of model parameters and their standard errors for the two-parameter item response theory (IRT) model using different estimation methods by Mplus. The second is to provide easily accessible information for practitioners, instructors, and students…
Descriptors: Item Response Theory, Computation, Factor Analysis, Statistical Analysis
Peer reviewed Peer reviewed
Direct linkDirect link
Devlieger, Ines; Talloen, Wouter; Rosseel, Yves – Educational and Psychological Measurement, 2019
Factor score regression (FSR) is a popular alternative for structural equation modeling. Naively applying FSR induces bias for the estimators of the regression coefficients. Croon proposed a method to correct for this bias. Next to estimating effects without bias, interest often lies in inference of regression coefficients or in the fit of the…
Descriptors: Regression (Statistics), Computation, Goodness of Fit, Statistical Inference
Peer reviewed Peer reviewed
Direct linkDirect link
Cao, Chunhua; Kim, Eun Sook; Chen, Yi-Hsin; Ferron, John; Stark, Stephen – Educational and Psychological Measurement, 2019
In multilevel multiple-indicator multiple-cause (MIMIC) models, covariates can interact at the within level, at the between level, or across levels. This study examines the performance of multilevel MIMIC models in estimating and detecting the interaction effect of two covariates through a simulation and provides an empirical demonstration of…
Descriptors: Hierarchical Linear Modeling, Structural Equation Models, Computation, Identification
Peer reviewed Peer reviewed
Direct linkDirect link
Isiordia, Marilu; Ferrer, Emilio – Educational and Psychological Measurement, 2018
A first-order latent growth model assesses change in an unobserved construct from a single score and is commonly used across different domains of educational research. However, examining change using a set of multiple response scores (e.g., scale items) affords researchers several methodological benefits not possible when using a single score. A…
Descriptors: Educational Research, Statistical Analysis, Models, Longitudinal Studies
Peer reviewed Peer reviewed
Direct linkDirect link
Hsiao, Yu-Yu; Kwok, Oi-Man; Lai, Mark H. C. – Educational and Psychological Measurement, 2018
Path models with observed composites based on multiple items (e.g., mean or sum score of the items) are commonly used to test interaction effects. Under this practice, researchers generally assume that the observed composites are measured without errors. In this study, we reviewed and evaluated two alternative methods within the structural…
Descriptors: Error of Measurement, Testing, Scores, Models
Peer reviewed Peer reviewed
Direct linkDirect link
Mao, Xiulin; Harring, Jeffrey R.; Hancock, Gregory R. – Educational and Psychological Measurement, 2015
Latent interaction models have motivated a great deal of methodological research, mainly in the area of estimating such models. Product-indicator methods have been shown to be competitive with other methods of estimation in terms of parameter bias and standard error accuracy, and their continued popularity in empirical studies is due, in part, to…
Descriptors: Structural Equation Models, Error of Measurement, Algebra, Statistical Analysis
Peer reviewed Peer reviewed
Direct linkDirect link
Devlieger, Ines; Mayer, Axel; Rosseel, Yves – Educational and Psychological Measurement, 2016
In this article, an overview is given of four methods to perform factor score regression (FSR), namely regression FSR, Bartlett FSR, the bias avoiding method of Skrondal and Laake, and the bias correcting method of Croon. The bias correcting method is extended to include a reliable standard error. The four methods are compared with each other and…
Descriptors: Regression (Statistics), Comparative Analysis, Structural Equation Models, Monte Carlo Methods
Peer reviewed Peer reviewed
Direct linkDirect link
Harring, Jeffrey R.; Weiss, Brandi A.; Li, Ming – Educational and Psychological Measurement, 2015
Several studies have stressed the importance of simultaneously estimating interaction and quadratic effects in multiple regression analyses, even if theory only suggests an interaction effect should be present. Specifically, past studies suggested that failing to simultaneously include quadratic effects when testing for interaction effects could…
Descriptors: Structural Equation Models, Statistical Analysis, Monte Carlo Methods, Computation
Peer reviewed Peer reviewed
Direct linkDirect link
von Eye, Alexander; Wiedermann, Wolfgang – Educational and Psychological Measurement, 2014
Approaches to determining direction of dependence in nonexperimental data are based on the relation between higher-than second-order moments on one side and correlation and regression models on the other. These approaches have experienced rapid development and are being applied in contexts such as research on partner violence, attention deficit…
Descriptors: Statistical Analysis, Factor Analysis, Structural Equation Models, Correlation
Previous Page | Next Page »
Pages: 1  |  2