SEM (Structural Equation Model); allowing the flexibility of Research Equation Model Using Path Analysis.

The unique art of research analysis depicts the usefulness of English Communication Skills, Logical perceptions for conceptualization, and the integration of Mathematics specifically the discipline of Statistics.  By combining the above disciplines, new knowledge can be generated for the advancement of technological ventures and the macro socioeconomic advancement.  Business ventures and capital markets of today are more dependent with research analysis data feeds via internet or maybe to other secured research company platform.  

Knowledge Management of a given company is an important tool in competing to the information dependent business models of today.  As such, quality research technique must be conducted to make sure that the research output from the conducted research is in accordance to the defined company problem at present giving the company the right business decisions towards the future of the business.

In my line of thinking, research is called an art because of the free interpretation and presentation of imaginative innovations supported with concrete statistical analysis.  The usual difficulty in any given research task is how to conceptualize the actual business ideas and problem into a statistical conceptual model.  Furthermore, writing and statistical disciplines will sometimes restrict the raw variables desired to be tested resulting to a misinformation of statistical output.  

Wrong research output will create wrong business decisions and forecasting. The method of Structural Equation Model (SEM) is allowing the imaginative concept of researchers to be put in a written conceptual model reducing the restrictions of logical reasoning and statistical rules.  Indeed, SEM is using the “Path Analysis” concept to allow the flow of ideas from the research writer.

Fundamental Rules of SEM:

The core concept of SEM is so suitable to any business research model because of the path Analysis concept using the raw variables as the observed and latent variables e.g. Variable A is the latent variable of Variable B, and Variable B is the latent variable of variable C.  Therefore, to simplify variable A & C are related if variable B is present in the series of variables.  

In a reverse model Variable C is the observed variable of Variable B, Likewise Variable B is the observed variable of Variable A.  Creating the SEM model, the above example can be calculated with the different statistical tools like Chi Square, Regression Analysis, ANOVA, & T-test.  Having SEM model strategy in calculating the perceived conceptual framework, a realistic conceptual structure of a known business research case can well present and analyzed in a statistical manner.