PLS를 활용한 고차요인구조 추정방법의 비교

• 영문명: A Comparison of Estimation Approaches of Structural Equation Model with Higher-Order Factors Using Partial Least Squares
• 발행기관: 한국산업경영시스템학회
• 저자명: 손기혁(Ki-Hyuk Son) 전영호(Young-Ho Chun) 옥창수(Chang-Soo Ok)
• 간행물 정보: 『산업경영시스템학회지』제36권 제4호, 64~70쪽, 전체 6쪽
• 주제분류: 경제경영 > 경영학
• 파일형태: PDF
• 발행일자: 2013.12.31

영문 초록

Estimation approaches for casual relation model with high-order factors have strict restrictions or limits. In the case of ML (Maximum Likelihood), a strong assumption which data must show a normal distribution is required and factors of exponentiation is impossible due to the uncertainty of factors. To overcome this limitation many PLS (Partial Least Squares) approaches are introduced to estimate the structural equation model including high-order factors. However, it is possible to yield biased estimates if there are some differences in the number of measurement variables connected to each latent variable. In addition, any approach does not exist to deal with general cases not having any measurement variable of high-order factors. This study compare several approaches including the repeated measures approach which are used to estimate the casual relation model including high-order factors by using PLS (Partial Least Squares), and suggest the best estimation approach. In other words, the study proposes the best approach through the research on the existing studies related to the casual relation model including high-order factors by using PLS and approach comparison using a virtual model.

목차

Abstract

1. 서론

2. PLS를 활용한 접근방법에 대한 고찰

3. 자료 수집 및 분석 방법

4. 각 접근방법의 비교

5. 연구결과 및 추후 연구방향

Acknowledgement

References

키워드

PLS Partial Least Squares High-Order Factors Structural Equation Model