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Gain More Insight from Common Latent Factor in Structural Equation Modeling

There is a great deal of evidence that method bias is really sure influences item validities, measurement error, correlation and covariance between latent constructs and thus leading the researchers to erroneous conclusion due to inflation or deflation during hypothesis testing. To remedy this, the...

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Main Authors: Asyraf, Afthanorhan, Zainudin, Awang, Norliana, Abd Majid, Hazimi, Foziah, Izzat, Ismail, Hussam, al Habusi, Tehseen, Shehnaz *
Format: Article
Language:English
Published: IOP 2021
Subjects:
Q Science (General)
Online Access:http://eprints.sunway.edu.my/1699/1/Shehnaz%20Gain%20more%20insight.pdf
http://eprints.sunway.edu.my/1699/
http://doi.org/10.1088/1742-6596/1793/1/012030
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spelling my.sunway.eprints.16992021-04-01T07:28:39Z http://eprints.sunway.edu.my/1699/ Gain More Insight from Common Latent Factor in Structural Equation Modeling Asyraf, Afthanorhan Zainudin, Awang Norliana, Abd Majid Hazimi, Foziah Izzat, Ismail Hussam, al Habusi Tehseen, Shehnaz * Q Science (General) There is a great deal of evidence that method bias is really sure influences item validities, measurement error, correlation and covariance between latent constructs and thus leading the researchers to erroneous conclusion due to inflation or deflation during hypothesis testing. To remedy this, the study provides a guideline to minimize the method bias in the context of structural equation modeling employing the covariance method (CB-SEM) using medical tourism model. A practical approach is illustrated for the identification of method bias based on the new construct namely common latent factor. Using this latent construct, we managed to identify which item has potential to permeate more variance from common latent factor. Nevertheless, we figure out that the method bias is do not exist in our developed model. Therefore, this measurement model is appropriate for structural model in order to achieve the research hypotheses. We hope that this discussion will help the researchers anticipate which items are likely exposed on method bias before proceed to advance modeling. IOP 2021 Article PeerReviewed text en cc_by_nc_4 http://eprints.sunway.edu.my/1699/1/Shehnaz%20Gain%20more%20insight.pdf Asyraf, Afthanorhan and Zainudin, Awang and Norliana, Abd Majid and Hazimi, Foziah and Izzat, Ismail and Hussam, al Habusi and Tehseen, Shehnaz * (2021) Gain More Insight from Common Latent Factor in Structural Equation Modeling. Journal of Physics: Conference Series, 1793 (1). 012030. ISSN 1742-6588 http://doi.org/10.1088/1742-6596/1793/1/012030 doi:10.1088/1742-6596/1793/1/012030
institution Sunway University
building Sunway Campus Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Sunway University
content_source Sunway Institutional Repository
url_provider http://eprints.sunway.edu.my/
language English
topic Q Science (General)
spellingShingle Q Science (General)
Asyraf, Afthanorhan
Zainudin, Awang
Norliana, Abd Majid
Hazimi, Foziah
Izzat, Ismail
Hussam, al Habusi
Tehseen, Shehnaz *
Gain More Insight from Common Latent Factor in Structural Equation Modeling
description There is a great deal of evidence that method bias is really sure influences item validities, measurement error, correlation and covariance between latent constructs and thus leading the researchers to erroneous conclusion due to inflation or deflation during hypothesis testing. To remedy this, the study provides a guideline to minimize the method bias in the context of structural equation modeling employing the covariance method (CB-SEM) using medical tourism model. A practical approach is illustrated for the identification of method bias based on the new construct namely common latent factor. Using this latent construct, we managed to identify which item has potential to permeate more variance from common latent factor. Nevertheless, we figure out that the method bias is do not exist in our developed model. Therefore, this measurement model is appropriate for structural model in order to achieve the research hypotheses. We hope that this discussion will help the researchers anticipate which items are likely exposed on method bias before proceed to advance modeling.
format Article
author Asyraf, Afthanorhan
Zainudin, Awang
Norliana, Abd Majid
Hazimi, Foziah
Izzat, Ismail
Hussam, al Habusi
Tehseen, Shehnaz *
author_facet Asyraf, Afthanorhan
Zainudin, Awang
Norliana, Abd Majid
Hazimi, Foziah
Izzat, Ismail
Hussam, al Habusi
Tehseen, Shehnaz *
author_sort Asyraf, Afthanorhan
title Gain More Insight from Common Latent Factor in Structural Equation Modeling
title_short Gain More Insight from Common Latent Factor in Structural Equation Modeling
title_full Gain More Insight from Common Latent Factor in Structural Equation Modeling
title_fullStr Gain More Insight from Common Latent Factor in Structural Equation Modeling
title_full_unstemmed Gain More Insight from Common Latent Factor in Structural Equation Modeling
title_sort gain more insight from common latent factor in structural equation modeling
publisher IOP
publishDate 2021
url http://eprints.sunway.edu.my/1699/1/Shehnaz%20Gain%20more%20insight.pdf
http://eprints.sunway.edu.my/1699/
http://doi.org/10.1088/1742-6596/1793/1/012030
_version_ 1696978738235834368
score 13.211869

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