NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 11 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Zsuzsa Bakk – Structural Equation Modeling: A Multidisciplinary Journal, 2024
A standard assumption of latent class (LC) analysis is conditional independence, that is the items of the LC are independent of the covariates given the LCs. Several approaches have been proposed for identifying violations of this assumption. The recently proposed likelihood ratio approach is compared to residual statistics (bivariate residuals…
Descriptors: Goodness of Fit, Error of Measurement, Comparative Analysis, Models
Peer reviewed Peer reviewed
Direct linkDirect link
E. Damiano D'Urso; Jesper Tijmstra; Jeroen K. Vermunt; Kim De Roover – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Measurement invariance (MI) is required for validly comparing latent constructs measured by multiple ordinal self-report items. Non-invariances may occur when disregarding (group differences in) an acquiescence response style (ARS; an agreeing tendency regardless of item content). If non-invariance results solely from neglecting ARS, one should…
Descriptors: Error of Measurement, Structural Equation Models, Construct Validity, Measurement Techniques
Peer reviewed Peer reviewed
Direct linkDirect link
Yuanfang Liu; Mark H. C. Lai; Ben Kelcey – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Measurement invariance holds when a latent construct is measured in the same way across different levels of background variables (continuous or categorical) while controlling for the true value of that construct. Using Monte Carlo simulation, this paper compares the multiple indicators, multiple causes (MIMIC) model and MIMIC-interaction to a…
Descriptors: Classification, Accuracy, Error of Measurement, Correlation
Peer reviewed Peer reviewed
Direct linkDirect link
Yang, Yanyun; Green, Samuel B. – Structural Equation Modeling: A Multidisciplinary Journal, 2010
Reliability can be estimated using structural equation modeling (SEM). Two potential problems with this approach are that estimates may be unstable with small sample sizes and biased with misspecified models. A Monte Carlo study was conducted to investigate the quality of SEM estimates of reliability by themselves and relative to coefficient…
Descriptors: Monte Carlo Methods, Structural Equation Models, Reliability, Sample Size
Peer reviewed Peer reviewed
Direct linkDirect link
Ferrando, Pere J.; Lorenzo-Seva, Urbano; Chico, Eliseo – Structural Equation Modeling: A Multidisciplinary Journal, 2009
This article proposes procedures for simultaneously assessing and controlling acquiescence and social desirability in questionnaire items. The procedures are based on a semi-restricted factor-analytic tridimensional model, and can be used with binary, graded-response, or more continuous items. We discuss procedures for fitting the model (item…
Descriptors: Factor Analysis, Response Style (Tests), Questionnaires, Test Items
Peer reviewed Peer reviewed
Direct linkDirect link
Yoon, Myeongsun; Millsap, Roger E. – Structural Equation Modeling: A Multidisciplinary Journal, 2007
In testing factorial invariance, researchers have often used a reference variable strategy in which the factor loading for a variable (i.e., reference variable) is fixed to 1 for identification. This commonly used method can be misleading if the chosen reference variable is actually a noninvariant item. This simulation study suggests an…
Descriptors: Item Analysis, Testing, Monte Carlo Methods, Structural Equation Models
Peer reviewed Peer reviewed
Direct linkDirect link
Bandalos, Deborah L. – Structural Equation Modeling: A Multidisciplinary Journal, 2008
This study examined the efficacy of 4 different parceling methods for modeling categorical data with 2, 3, and 4 categories and with normal, moderately nonnormal, and severely nonnormal distributions. The parceling methods investigated were isolated parceling in which items were parceled with other items sharing the same source of variance, and…
Descriptors: Structural Equation Models, Computation, Goodness of Fit, Classification
Peer reviewed Peer reviewed
Direct linkDirect link
Sass, Daniel A.; Smith, Philip L. – Structural Equation Modeling: A Multidisciplinary Journal, 2006
Structural equation modeling allows several methods of estimating the disattenuated association between 2 or more latent variables (i.e., the measurement model). In one common approach, measurement models are specified using item parcels as indicators of latent constructs. Item parcels versus original items are often used as indicators in these…
Descriptors: Structural Equation Models, Item Analysis, Error of Measurement, Measures (Individuals)
Peer reviewed Peer reviewed
Direct linkDirect link
Tsai, Tien-Lung; Shau, Wen-Yi; Hu, Fu-Chang – Structural Equation Modeling: A Multidisciplinary Journal, 2006
This article generalizes linear path analysis (PA) and simultaneous equations models (SiEM) to deal with mixed responses of different types in a recursive or triangular system. An efficient instrumental variable (IV) method for estimating the structural coefficients of a 2-equation partially recursive generalized path analysis (GPA) model and…
Descriptors: Structural Equation Models, Path Analysis, Simulation, Equations (Mathematics)
Peer reviewed Peer reviewed
Direct linkDirect link
Kim, Sooyeon; Hagtvet, Knut A. – Structural Equation Modeling: A Multidisciplinary Journal, 2003
This study focused on misspecifications in composing parcels to represent a latent construct. Two measurement design factors, item reliability and intercorrelations among parcels, defined 12 true unidimensional parcel models. Deviations from the true model were examined via a 2-facet measurement model in which items and parcels represented the 2…
Descriptors: Simulation, Factor Structure, Measurement Techniques, Goodness of Fit
Peer reviewed Peer reviewed
Direct linkDirect link
Noar, Seth M. – Structural Equation Modeling: A Multidisciplinary Journal, 2003
Across a variety of disciplines and areas of inquiry, reliable and valid measures are a cornerstone of quality research. This is the case because to have confidence in the findings of our studies, we must first have confidence in the quality of our measures. This article briefly reviews the literature on scale development and provides an empirical…
Descriptors: Measures (Individuals), Factor Analysis, Structural Equation Models, Test Validity