scholarly journals Testing strong factorial invariance using three-level structural equation modeling

2014 ◽  
Vol 5 ◽  
Author(s):  
Suzanne Jak
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Factorial Invariance ◽  
Equation Modeling

New developments in latent variable panel analyses of longitudinal data

2007 ◽  
Vol 31 (4) ◽  
pp. 357-365 ◽  
Author(s):  
Todd D. Little ◽  
Kristopher J. Preacher ◽  
James P. Selig ◽  
Noel A. Card
Keyword(s):  
Structural Equation Modeling ◽  
Longitudinal Data ◽  
Latent Variables ◽  
Latent Variable ◽  
Structural Equation ◽  
Null Model ◽  
Factorial Invariance ◽  
Equation Modeling ◽  
New Developments ◽  
Mediated Effects

We review fundamental issues in one traditional structural equation modeling (SEM) approach to analyzing longitudinal data — cross-lagged panel designs. We then discuss a number of new developments in SEM that are applicable to analyzing panel designs. These issues include setting appropriate scales for latent variables, specifying an appropriate null model, evaluating factorial invariance in an appropriate manner, and examining both direct and indirect (mediated), effects in ways better suited for panel designs. We supplement each topic with discussion intended to enhance conceptual and statistical understanding.

scholarly journals Passion Scale: Psychometric Properties and Factorial Invariance via Exploratory Structural Equation Modeling (ESEM)

2019 ◽  
Vol 29 ◽  
Author(s):  
Evandro Morais Peixoto ◽  
Tatiana de Cássia Nakano ◽  
Ricardo Almeida Castillo ◽  
Leonardo Pestillo Oliveira ◽  
Marcos Alencar Abaide Balbinotti
Keyword(s):  
Structural Equation Modeling ◽  
Psychometric Properties ◽  
Structural Equation ◽  
Measurement Model ◽  
Factorial Invariance ◽  
Equation Modeling ◽  
Exploratory Structural Equation Modeling ◽  
Brazilian Version ◽  
Theoretical Hypothesis ◽  
Adaptation Processes

Abstract Passion is an important element among the psychological processes involved in the performance of any activity, including sports practice. Given the scarcity of nationally valid and reliable instruments, this study has the purpose of presenting the adaptation processes of the Passion Scale to the Brazilian context. A total of 789 Brazilian athletes (age:16.62±3.20; 58.4% men) participated in the study. To evaluate their psychometric properties, the scale dimensionality was estimated through the Hull method and Exploratory Structural Equation Modeling, and the accuracy by composite reliability. The factorial invariance model was estimated between men and women, and between participants of different competitive levels. Results showed the two-factor structure of the scale, according to the theoretical hypothesis, with desirable accuracy indicators. Equivalence of the measurement model was demonstrated when evaluating participants of different sexes and different competitive levels. Results suggest adequacy of the Brazilian version for the evaluation of this construct.

Evaluating Factorial Invariance: An Interval Estimation Approach Using Bayesian Structural Equation Modeling

2018 ◽  
Vol 54 (2) ◽  
pp. 224-245 ◽  
Author(s):  
Dexin Shi ◽  
Hairong Song ◽  
Christine DiStefano ◽  
Alberto Maydeu-Olivares ◽  
Heather L. McDaniel ◽  
...  
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Interval Estimation ◽  
Factorial Invariance ◽  
Equation Modeling ◽  
Bayesian Structural Equation Modeling

scholarly journals Competence in Medical Practice as Perceived by Malaysian Medical Interns: A Measurement Invariance Analysis

2012 ◽  
Vol 3 (7) ◽  
pp. 225-233 ◽  
Author(s):  
Abideen Adeyemi Adewale ◽  
Azura Omar .
Keyword(s):  
Structural Equation Modeling ◽  
Statistical Analysis ◽  
Medical School ◽  
Medical Practice ◽  
Structural Equation ◽  
Patient Management ◽  
Clinical Skills ◽  
Factorial Invariance ◽  
Equation Modeling ◽  
Survey Questionnaire

This study investigates the perception of Malaysian housemen on what the indicators of competence are in the medical practice. This derives from the need for the interns to have the requisite skill needed to make them competent in the post-medical school medical practice. A survey questionnaire was administered on all 2,046 housemen in all medical schools across Malaysia as at April 30, 2008 when data was collected. Data so obtained were subjected to statistical analysis based on N=1213 using both the structural equation modeling via SPSS AMOS 18 software. Nine skills were identified in all. These are interpersonal, IT, patient management, basic, holistic, science, ethics, coping, and clinical skills. While all the skills were found to be statistically significant, no factorial invariance was observed when the data is split into demographic divides.

Testing the Assumption of Uncorrelated Errors for Short Scales by Means of Structural Equation Modeling

2014 ◽  
Vol 35 (4) ◽  
pp. 201-211 ◽  
Author(s):  
André Beauducel ◽  
Anja Leue
Keyword(s):  
Structural Equation Modeling ◽  
Negative Correlation ◽  
Structural Equation ◽  
Error Score ◽  
Classical Test Theory ◽  
Test Theory ◽  
Equation Modeling ◽  
Eysenck Personality Questionnaire ◽  
Personality Questionnaire ◽  
True Score

It is shown that a minimal assumption should be added to the assumptions of Classical Test Theory (CTT) in order to have positive inter-item correlations, which are regarded as a basis for the aggregation of items. Moreover, it is shown that the assumption of zero correlations between the error score estimates is substantially violated in the population of individuals when the number of items is small. Instead, a negative correlation between error score estimates occurs. The reason for the negative correlation is that the error score estimates for different items of a scale are based on insufficient true score estimates when the number of items is small. A test of the assumption of uncorrelated error score estimates by means of structural equation modeling (SEM) is proposed that takes this effect into account. The SEM-based procedure is demonstrated by means of empirical examples based on the Edinburgh Handedness Inventory and the Eysenck Personality Questionnaire-Revised.

The Measurement Invariance of the Short Dark Triad

2020 ◽  
Vol 41 (4) ◽  
pp. 207-218
Author(s):  
Mihaela Grigoraș ◽  
Andreea Butucescu ◽  
Amalia Miulescu ◽  
Cristian Opariuc-Dan ◽  
Dragoș Iliescu
Keyword(s):  
Structural Equation Modeling ◽  
Item Response ◽  
Structural Equation ◽  
Dark Triad ◽  
Theory And Practice ◽  
Equation Modeling ◽  
Scale Level ◽  
High Stake ◽  
Differential Functioning ◽  
Item Functioning

Abstract. Given the fact that most of the dark personality measures are developed based on data collected in low-stake settings, the present study addresses the appropriateness of their use in high-stake contexts. Specifically, we examined item- and scale-level differential functioning of the Short Dark Triad (SD3; Paulhus & Jones, 2011 ) measure across testing contexts. The Short Dark Triad was administered to applicant ( N = 457) and non-applicant ( N = 592) samples. Item- and scale-level invariances were tested using an Item Response Theory (IRT)-based approach and a Structural Equation Modeling (SEM) approach, respectively. Results show that more than half of the SD3 items were flagged for Differential Item Functioning (DIF), and Exploratory Structural Equation Modeling (ESEM) results supported configural, but not metric invariance. Implications for theory and practice are discussed.

Childhood Intelligence Predicts Adult Trait Openness

2016 ◽  
Vol 37 (2) ◽  
pp. 105-111 ◽  
Author(s):  
Adrian Furnham ◽  
Helen Cheng
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Social Background ◽  
Study Data ◽  
Equation Modeling ◽  
Direct Effects ◽  
Data Set ◽  
National Child Development Study ◽  
Nationally Representative ◽  
The Uk

Abstract. This study used a longitudinal data set of 5,672 adults followed for 50 years to determine the factors that influence adult trait Openness-to-Experience. In a large, nationally representative sample in the UK (the National Child Development Study), data were collected at birth, in childhood (age 11), adolescence (age 16), and adulthood (ages 33, 42, and 50) to examine the effects of family social background, childhood intelligence, school motivation during adolescence, education, and occupation on the personality trait Openness assessed at age 50 years. Structural equation modeling showed that parental social status, childhood intelligence, school motivation, education, and occupation all had modest, but direct, effects on trait Openness, among which childhood intelligence was the strongest predictor. Gender was not significantly associated with trait Openness. Limitations and implications of the study are discussed.

Sign in / Sign up

Export Citation Format

Share Document