The Genesis

The field of Research is ever evolving and various new techniques continuously emerge for enhancing the quality of research. For superior research output in Social Science in general and Management in particular, it is imperative to be abreast of such developments. Various new software have come in to facilitate and fasten the research data calculation and analysis which not just helps the accuracy of the calculations but also brings forth newer perspectives to the research.

Structural Equation Modelling (SEM) is a statistical technique for testing and estimating causal relations using a combination of statistical data and qualitative causal assumptions. SEM allows both confirmatory and exploratory modelling, meaning they are suited to both theory testing and theory development. Confirmatory modeling usually starts out with a hypothesis that gets represented in a causal model. The concepts used in the model must then operationalize to allow testing of the relationships between the concepts in the model. The model is tested against the obtained measurement data to determine how well the model fits the data. The causal assumptions embedded in the model often have falsifiable implications which can be tested against the data.

With an initial theory SEM can be used inductively by specifying a corresponding model and using data to estimate the values of free parameters. Often the initial hypothesis requires adjustment in light of model evidence. When SEM is used purely for exploration, this is usually in the context of exploratory factor analysis as in psychometric design.

Among the strengths of SEM is the ability to construct latent variables: variables which are not measured directly, but are estimated in the model from several measured variables each of which is predicted to 'tap into' the latent variables. This allows the modeler to explicitly capture the unreliability of measurement in the model, which in theory allows the structural relations between latent variables to be accurately estimated. Factor analysis, path analysis and regression all represent special cases of SEM.

Topics to be covered:
Exploratory Factor Analysis, Regression Analysis, Graphical Models, Confirmatory Factor Analysis, Structural Models.

Methodology:
Theoretical inputs, Tutorial on LISREL, Discussion of SPSS and LISREL Outputs for the topics included in the workshop.