Nature of Multidimensional Constructs Represented by Item Parcels in Structural Equation Modeling

碩士 === 國立臺灣大學 === 心理學研究所 === 105 === Item parcels, represented as summation or average over items, can be used as indicators of latent variables in structural equation modeling (SEM). Little et al. (2013) and Cole et al. (2016) indicated that the nature of multidimensional constructs represented by...

Full description

Bibliographic Details
Main Authors: Yo-Lin Chen, 陳宥霖
Other Authors: 翁儷禎
Format: Others
Language:zh-TW
Published: 2017
Online Access:http://ndltd.ncl.edu.tw/handle/5wv88j
Description
Summary:碩士 === 國立臺灣大學 === 心理學研究所 === 105 === Item parcels, represented as summation or average over items, can be used as indicators of latent variables in structural equation modeling (SEM). Little et al. (2013) and Cole et al. (2016) indicated that the nature of multidimensional constructs represented by parcels can be different from that assumed by the researchers and thus affects the results of SEM analysis. Researchers should therefore examine the nature of multidimensional constructs represented by parcels prior to the analysis. Cole et al. and Williams and O’Boyle (2008) indicated that many of the constructs investigated in psychological research are multidimensional, consisting of several facets, and item parcels have been frequently adopted to be indicators for these constructs in SEM. The present study therefore extended the algebraic derivation of the covariance matrix of item parcels in Sterba & MacCallum (2010) from unidimensional to multidimensional constructs to provide a theoretical framework for examining the nature of multidimensional constructs implied by parcels. The effects of parceling strategy, correlations among facets, and factorial complexity of items on the nature of multidimensional constructs represented by parcels were discussed using this framework and illustrated by a numerical simulation example. Researchers may apply the framework proposed in this study to clarify the nature of the multidimensional constructs inferred from item parcels through examining the covariance matrix among parcels so as to avoid misleading results from SEM analysis.