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Structural equation modeling in social science research Issues of validity and reliability in the research process

Structural equation modeling in social science research Issues of validity and reliability in the... Purpose – The purpose of this paper is to describe and discuss a few principal and crucial steps of “antecedents” and “postcedents” in relation to structural equation modeling (SEM) in social science research. Design/methodology/approach – This paper is based upon a conceptual and reflective discussion of SEM in social sciences research. Findings – SEM is not science per se , but just a tool that is used to extract meaning from the previous steps of research processes in terms of a research phenomenon in focus. Research limitations/implications – Based upon the steps of validity and reliability discussed in relation to predetermined measurement and structural models in SEM, application implications are provided. Practical implications – Like many statistical tools, SEM can be misused to manipulate findings and fit of measurement and structural models. Researchers may become more interested in the tool than in the subject matter. Originality/value – Using SEM does not elevate research to be science or make the researcher a scientist! An area of concern for further debate is whether the widespread and variable applications of SEM in social science (in particular, marketing) research are all science. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png European Business Review Emerald Publishing

Structural equation modeling in social science research Issues of validity and reliability in the research process

Barry J. Babin; Göran Svensson
European Business Review , Volume 24 (4): 11 – Jun 22, 2012
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Publisher
Emerald Publishing
Copyright
Copyright © 2012 Emerald Group Publishing Limited. All rights reserved.
ISSN
0955-534X
DOI
10.1108/09555341211242132
Publisher site
See Article on Publisher Site

Abstract

Purpose – The purpose of this paper is to describe and discuss a few principal and crucial steps of “antecedents” and “postcedents” in relation to structural equation modeling (SEM) in social science research. Design/methodology/approach – This paper is based upon a conceptual and reflective discussion of SEM in social sciences research. Findings – SEM is not science per se , but just a tool that is used to extract meaning from the previous steps of research processes in terms of a research phenomenon in focus. Research limitations/implications – Based upon the steps of validity and reliability discussed in relation to predetermined measurement and structural models in SEM, application implications are provided. Practical implications – Like many statistical tools, SEM can be misused to manipulate findings and fit of measurement and structural models. Researchers may become more interested in the tool than in the subject matter. Originality/value – Using SEM does not elevate research to be science or make the researcher a scientist! An area of concern for further debate is whether the widespread and variable applications of SEM in social science (in particular, marketing) research are all science.

Journal

European Business Review – Emerald Publishing

Published: Jun 22, 2012

Keywords: Structural equation modeling; Reliability; Validity; Research process; Social science; Sciences; Research

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