| _version_ |
1860799656547581952
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| building |
INTELEK Repository
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| collection |
Online Access
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| collectionurl |
https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072
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| date |
2017-09-07 14:47:42
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| eventvenue |
Primula Beach Hotel Kuala Terengganu, Terengganu
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| format |
Restricted Document
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| id |
6876
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UniSZA
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| originalfilename |
1529-01-FH03-FESP-17-09949.jpg
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| person |
norman
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| recordtype |
oai_dc
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| resourceurl |
https://intelek.unisza.edu.my/intelek/pages/view.php?ref=6876
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| spelling |
6876 https://intelek.unisza.edu.my/intelek/pages/view.php?ref=6876 https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072 Restricted Document Conference Conference Paper image/jpeg inches 96 96 norman 59 59 1436 766 2017-09-07 14:47:42 1436x766 1529-01-FH03-FESP-17-09949.jpg UniSZA Private Access The development of comparative bias index Structural Equation Modeling (SEM) is a second generation statistical analysis techniques developed for analyzing the inter-relationships among multiple variables in a model simultaneously. There are two most common used methods in SEM namely Covariance-Based Structural Equation Modeling (CB-SEM) and Partial Least Square Path Modeling (PLS-PM). There have been continuous debates among researchers in the use of PLS-PM over CB-SEM. While there is few studies were conducted to test the performance of CB-SEM and PLS-PM bias in estimating simulation data. This study intends to patch this problem by a) developing the Comparative Bias Index and b) testing the performance of CB-SEM and PLS-PM using developed index. Based on balanced experimental design, two multivariate normal simulation data with of distinct specifications of size 50, 100, 200 and 500 are generated and analyzed using CB-SEM and PLS-PM. 24th National Symposium on Mathematical Sciences: Mathematical Sciences Exploration for the Universal Preservation, Primula Beach Hotel Kuala Terengganu, Terengganu
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| spellingShingle |
The development of comparative bias index
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| summary |
Structural Equation Modeling (SEM) is a second generation statistical analysis techniques developed for analyzing the inter-relationships among multiple variables in a model simultaneously. There are two most common used methods in SEM namely Covariance-Based Structural Equation Modeling (CB-SEM) and Partial Least Square Path Modeling (PLS-PM). There have been continuous debates among researchers in the use of PLS-PM over CB-SEM. While there is few studies were conducted to test the performance of CB-SEM and PLS-PM bias in estimating simulation data. This study intends to patch this problem by a) developing the Comparative Bias Index and b) testing the performance of CB-SEM and PLS-PM using developed index. Based on balanced experimental design, two multivariate normal simulation data with of distinct specifications of size 50, 100, 200 and 500 are generated and analyzed using CB-SEM and PLS-PM.
|
| title |
The development of comparative bias index
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| title_full |
The development of comparative bias index
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| title_fullStr |
The development of comparative bias index
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| title_full_unstemmed |
The development of comparative bias index
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| title_short |
The development of comparative bias index
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| title_sort |
development of comparative bias index
|