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Assessing measurement model quality in PLS-SEM using confirmatory composite analysis
, 2020Confirmatory factor analysis (CFA) has historically been used to develop and improve reflectively measured constructs based on the domain sampling model.
Joseph F. Hair +2 more
semanticscholar +1 more source
Reviewer Resources: Confirmatory Factor Analysis
Organizational Research Methods, 2022Confirmatory factor analyses (CFA) are widely used in the organizational literature. As a result, understanding how to properly conduct these analyses, report the results, and interpret their implications is critically important for advancing ...
Christopher D. Nye
semanticscholar +1 more source
Quality 4.0 – a measurement model using the confirmatory factor analysis (CFA) approach
International Journal of Quality & Reliability Management, 2021PurposeThe disruptions caused by new-age technologies of Industry 4.0 are posing a formidable challenge to researchers, academicians and practitioners alike.
G. Sureshchandar
semanticscholar +1 more source
Foreign language enjoyment: a longitudinal confirmatory factor analysis–curve of factors model
Journal of Multilingual and Multicultural Development, 2021In an attempt to measure the dynamic features of foreign language enjoyment (FLE), we adopted a longitudinal confirmatory factor analysis-curve of factors model (LCFA-CFM) approach to substantiate the validity of the original FLE scale (Dewaele and ...
Majid Elahi Shirvan +2 more
semanticscholar +1 more source
1988
Exploratory and confirmatory factor analysis reflect respectively two different approaches to the philosophy of science. To understand the differences between these two approaches, we must first consider their philosophical background.
Ira H. Bernstein +2 more
openaire +2 more sources
Exploratory and confirmatory factor analysis reflect respectively two different approaches to the philosophy of science. To understand the differences between these two approaches, we must first consider their philosophical background.
Ira H. Bernstein +2 more
openaire +2 more sources
Multivariate Behavioral Research, 2020
CFAs of multidimensional constructs often fail to meet standards of good measurement (e.g., goodness-of-fit, measurement invariance, and well-differentiated factors).
H. Marsh +4 more
semanticscholar +1 more source
CFAs of multidimensional constructs often fail to meet standards of good measurement (e.g., goodness-of-fit, measurement invariance, and well-differentiated factors).
H. Marsh +4 more
semanticscholar +1 more source
Item Meaning and Order as Causes of Correlated Residuals in Confirmatory Factor Analysis
Structural Equation Modeling: A Multidisciplinary Journal, 2021In this study I examined the oft-made claim that correlated residuals result from similarities in item meaning. I also investigated the degree to which administering items with similar meaning or wording in a random, rather than a contiguous order would ...
D. Bandalos
semanticscholar +1 more source
Nurse Education Today, 2020
AIM The study aimed to establish the role played by technology in nursing education through Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA).
A. Harerimana, N. Mtshali
semanticscholar +1 more source
AIM The study aimed to establish the role played by technology in nursing education through Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA).
A. Harerimana, N. Mtshali
semanticscholar +1 more source
Indicators per Factor in Confirmatory Factor Analysis: More is not Always Better
Structural Equation Modeling: A Multidisciplinary Journal, 2020Although some research in confirmatory factor analysis has suggested that more indicators per factor are generally better, studies have also documented that sample size requirements increase as model size increases.
Jennifer Koran
semanticscholar +1 more source
Fit Indices in Structural Equation Modeling and Confirmatory Factor Analysis: Reporting Guidelines
Asian Journal of Economics Business and AccountingThis research explores the essential aspects of reporting fit indices in Structural Equation Modeling (SEM), focusing on their significance, methodologies for evaluation, and implications for model validity.
S. S, T. Mohanasundaram
semanticscholar +1 more source