Please use this identifier to cite or link to this item: https://ah.nccu.edu.tw/handle/140.119/118984


Title: CB-SEM和PLS-SEM在估計交互作用效果之比較
The comparison of estimation accuracy in interaction effect between CB-SEM and PLS-SEM
Authors: 李昭鋆
Lee, Chao-Yun
Contributors: 余民寧
Yu, Ming-Ning
李昭鋆
Lee, Chao-Yun
Keywords: CB-SEM
PLS-SEM
交互作用
CB-SEM
PLS-SEM
Interaction effect
Date: 2018
Issue Date: 2018-07-27 12:41:33 (UTC+8)
Abstract: 本研究研究目的主要在於瞭解CB-SEM和PLS-SEM之指標乘積法、正交法、二階段法、無限制法在結構方程式模型之交互作用中,對迴歸係數、因素負荷量、解釋量、因素分數估計結果之良窳;此外,並瞭解指標數目、人數、資料類型對估計之影響。故本研究之實驗情況,共分三種指標數目、九種人數、二種資料類型,合計五十四種類型,並在每一類型模擬五百次。研究結果顯示,以整體論,在大部份的情況下,CB-SEM在迴歸係數、解釋量、因素負荷量表現較佳,而PLS-SEM在估計因素分數上較佳。而精確來說,若研究目的乃欲精確估計因數分數,則三百人、四題以上,建議採取PLS-SEM二階段法;若研究目是在精確估計迴歸係數、解釋量,若人數在四百人以上,建議採用CB-SEM無限制法。另外,本研究亦發現在大部份的情況下,指標數目愈多,資料型態為連續型態者,其估計效果愈佳。
The purpose of this study is to find out the results of estimation about interaction effects. The estimations come from the product indicator, two stage, orthogonalizing, and unconstrained approach which are estimated by CB-SEM and PLS-SEM separately. In the research, regression coefficient, factor loading, factor score, and r square are calculated by eight kinds of methods. Besides, night kinds of sample sizes, three kinds of number of indicators, and two kinds of data types are also studied to realize how they influence the estimations. Therefore, there are fifty-four situations. The results show that the estimation of regression coffoeicient, r square and factor loading are excellent by CB-SEM, but the estimation of factor score is better by PLS-SEM under most situations. If the object is to estimate the factor score, two satge approach of PLS-SEM is suggested based on the condition of sample size larger than 300 and 4 indicators. However, if the aim is to estimate the regression coffoeicient , r square, or factor loading, the unconstrained method of CB-SEM is the best choice when sample size is larger than 400. In addition, the continuous data type and more numbers of indicators are good for estimation under most conditions.
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Description: 博士
國立政治大學
教育學系
102152502
Source URI: http://thesis.lib.nccu.edu.tw/record/#G1021525021
Data Type: thesis
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