In this module we will cover the basics of exploratory factor analysis (EFA), some theoretical inputs about the method, and then discuss how to conduct it using SPSS.
Structural Equation Modeling (SEM) is a statistical methodology that is widely used in social sciences research (especially marketing, organizational behavior, human resource management, psychology, behavioral finance and behavioral economics). SEM was introduced in 1970s and combines psychometrics with econometrics. On the psychometric side, SEM allows for latent variables with multiple indicators. On the econometric side, SEM allows for multiple equations, possibly with feedback loops. SEM models are so general that they encompass most of the statistical methods that are currently used in the social and behavioral sciences. SEM allows a researcher to test complex models with multiple pathways, model latent variables with multiple indicators, investigate mediation and moderation in a systematic way and adjust for measurement error in predictor variables. This lecture series shall provide the audience a general introduction to Covariance-Based SEM (CB-SEM). The series will be based on a combination of theoretical and practice-oriented sessions that will provide working knowledge of AMOS, a statistical software.
This module presents videos on doing structural equation modeling (SEM) analysis using AMOS. The module presents videos on SEM basics, understanding degrees of freedom, measurement models, testing discriminant validity, nomological validity testing, and item parceling.
In this blog I present details of my youtube videos where viewers can learn working on AMOS, a Structural Equation Modeling software by IBM. The details of the data files, video lectures and of other videos in my lecture series on 'Psychometrics' are also presented.
The workshop focused on developing understanding of conditional process analysis and learning about the ways to test them. Although these concepts are fairly simple, the statistical issues that arise in estimating and testing mediation and moderation effects turn out to be rather complex and subtle.
In the first part (first five lectures) of Module 3, I talk about the concept of reliability, why is reliability computed and its use in research in social sciences. n the second part (lecture 6 onwards) of this module, I explain the theory of factor analyses (EFA - exploratory factor analysis and CFA - confirmatory factor analysis).
Module covers aspects of reflective and formative constructs. Also, I would be talking about the steps to be followed while developing items for scales used in social science research.