The use of partial least squares path modeling in causal inference for archival financial accounting research

The use of partial least squares path modeling in causal inference for archival financial accounting research

In financial accounting research, multivariate regression is almost exclusively the dominant statistical method. By contrast, Partial Least Squares path modeling is a under-utilized statistical method. The aim of this study is to examine how Partial Least Squares path modeling can be applied to the...

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Bibliographic Details
Main Authors: Goh, Chinfei, Ali, Mohammad Bilal, Md. Rasli, Amran
Format: Article
Language:English
English
Published: Penerbit UTM Press 2014
Subjects:
LB Theory and practice of education
Online Access:http://eprints.utm.my/id/eprint/63038/1/MohammadBilalali2014_TheuseofPartialLeastSquares.pdf
http://eprints.utm.my/id/eprint/63038/7/MohammadBilalali2014_TheuseofPartialLeastSquares.pdf
http://eprints.utm.my/id/eprint/63038/
http://dx.doi.org/10.11113/jt.v68.2930
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Institution: Universiti Teknologi Malaysia
Language: English
English
Description
Summary:In financial accounting research, multivariate regression is almost exclusively the dominant statistical method. By contrast, Partial Least Squares path modeling is a under-utilized statistical method. The aim of this study is to examine how Partial Least Squares path modeling can be applied to the archival financial accounting research. This article first presents an overview on multivariate regression and structural equation modeling. The authors then highlight that advantages of using Partial Least Squares path modeling to address the research constraints in causal inference for archival financial accounting research.

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