Role Of Structural Equation Modelling In Theory Testing And Development

Structural equation modelling (SEM) is a popular statistical technique for testing and estimating causal relations using a combination of statistical data and qualitative causal assumptions, which are typically based on a theory. This technique is widely used by social scientists for theory testing and development. SEM is a combination of factor analysis and multiple-regression and it includes path analysis and confirmatory factor analysis. SEM helps researchers to generate and test hypotheses about relationships among theoretical constructs. The tight specification model in SEM makes it a uniquely powerful statistical tool. SEM can help a researcher answer substantive questions and validate measurements. This chapter is intended to provide an overview and some insights to readers as to how SEM works and what are its benefits to a social scientist. We discuss AMOS procedure and several aspects of SEM including model identification, specification, estimation, and modification as well as issues of sample size and interpretation and communication of results. We illustrate many of the key ideas and concepts pertaining to SEM by providing an example.