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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: Afthanorhan, Asyraf, Awang, Zainudin, Abd Majid, Norliana, Foziah, Hazimi, Ismail, Izzat, Al Halbusi, Hussam, Tehseen, Shehnaz
Format: Conference or Workshop Item
Published: 2021
Subjects:
QA Mathematics
Online Access:http://eprints.um.edu.my/35673/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85103080561&doi=10.1088%2f1742-6596%2f1793%2f1%2f012030&partnerID=40&md5=897b2002e1694b4355e1c5ba51cfa37d
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spelling my.um.eprints.356732023-11-27T07:06:52Z http://eprints.um.edu.my/35673/ Gain more insight from common latent factor in structural equation modeling Afthanorhan, Asyraf Awang, Zainudin Abd Majid, Norliana Foziah, Hazimi Ismail, Izzat Al Halbusi, Hussam Tehseen, Shehnaz QA Mathematics 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. © Published under licence by IOP Publishing Ltd. 2021-03 Conference or Workshop Item PeerReviewed Afthanorhan, Asyraf and Awang, Zainudin and Abd Majid, Norliana and Foziah, Hazimi and Ismail, Izzat and Al Halbusi, Hussam and Tehseen, Shehnaz (2021) Gain more insight from common latent factor in structural equation modeling. In: 1st International Recent Trends in Technology, Engineering and Computing Conference, IRTTEC 2020, 30 September 2020, Kuala Lumpur, Virtual. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85103080561&doi=10.1088%2f1742-6596%2f1793%2f1%2f012030&partnerID=40&md5=897b2002e1694b4355e1c5ba51cfa37d
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic QA Mathematics
spellingShingle QA Mathematics
Afthanorhan, Asyraf
Awang, Zainudin
Abd Majid, Norliana
Foziah, Hazimi
Ismail, Izzat
Al Halbusi, Hussam
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. © Published under licence by IOP Publishing Ltd.
format Conference or Workshop Item
author Afthanorhan, Asyraf
Awang, Zainudin
Abd Majid, Norliana
Foziah, Hazimi
Ismail, Izzat
Al Halbusi, Hussam
Tehseen, Shehnaz
author_facet Afthanorhan, Asyraf
Awang, Zainudin
Abd Majid, Norliana
Foziah, Hazimi
Ismail, Izzat
Al Halbusi, Hussam
Tehseen, Shehnaz
author_sort Afthanorhan, Asyraf
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
publishDate 2021
url http://eprints.um.edu.my/35673/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85103080561&doi=10.1088%2f1742-6596%2f1793%2f1%2f012030&partnerID=40&md5=897b2002e1694b4355e1c5ba51cfa37d
_version_ 1783876626696634368
score 13.211869

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