These are the variables that are not directly measured or observed; a set of observed variables are used to define or infer the latent variable or construct (e.g., intelligence). Variables either if they are observed or latent, they can be defined as independent variables or dependent variables based on researchers’ interest.
Published in Chapter:
An Overview of Structural Equation Modeling and Its Application in Social Sciences Research
Sai Priyanka Pagadala (Indian Agricultural Research Institute, New Delhi, India), Sangeetha V. (Indian Agricultural Research Institute, New Delhi, India), Venkatesh P. (Indian Agricultural Research Institute, New Delhi, India), and Girish Kumar Jha (Indian Agricultural Research Institute, New Delhi, India)
Copyright: © 2023
|Pages: 19
DOI: 10.4018/978-1-6684-6859-3.ch010
Abstract
Social science research deals with the highly complex phenomenon guided by various latent and interrelated constructs. As these constructs are invisible and not directly measurable, social scientists employ highly sophisticated multivariate analytical techniques that can simplify a complex data pattern to derive meaningful conclusions. Structural equation modeling (SEM) is a methodology used to represent, estimate, and test a network of relationships among variables. It is an integrated model for hypothesis testing and constructs' validity. This chapter deals with the various aspects of the SEM methodology, starting from describing the statistical algorithms used, the role of theory, measurement and structural model, stages in testing model validity, etc., meticulously explained in simple terms to provide with a basic understanding of this intricate technique.