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, th...
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| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
2021
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| Subjects: | |
| Online Access: | http://eprints.unisza.edu.my/4821/1/FH03-FPP-20-47929.pdf http://eprints.unisza.edu.my/4821/2/FH03-FPP-21-51992.pdf http://eprints.unisza.edu.my/4821/ |
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| Institution: | Universiti Sultan Zainal Abidin |
| Language: | English English |
| Summary: | 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. |
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