Structural Equation Modelling

Prerequisites

Bookings for this module open on THURSDAY, 11 DECEMBER at 10:00 am
For more information see: http://www.ssrmc.group.cam.ac.uk/ssrmc-modules/core/making/windows

This module is part of the Social Science Research Methods Centre training programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences.

Structural Equation Modelling (SEM), also known as analysis of covariance structures, is a powerful statistical methodology that takes confirmatory approach to the analysis of various datasets usually collected in the Social Sciences. SEM simultaneously uses techniques from multiple regression, path analysis, and factor analyses. Based on these techniques researchers can test theories/hypotheses for their work. In the course, we will use the statistical package AMOS to generate and test models. This course will offer a basic introduction to SEM, but participants will be able further develop their knowledge in SEM from this foundation.

• Mphil and PhD students from participating departments taking the Social Science Research Methods Centre training programme as part of their research degree

• Strong background in basic statistical techniques, particularly in multivariate regression and factor analysis
• A University Information Services (Computing) Desktop Services password (http://www.ucs.cam.ac.uk/linkpages/newcomers)
• Access to CamTools

Number of sessions: 4

• Introduction to SEM and AMOS programming
• CFA and Path Analysis
• Fitting and models and model identification
• Model testing with AMOS and workshop with own data

To offer a basic introduction to SEM from which participants will be able to further develop their knowledge.

Presentations, demonstrations and practicals

SPSS and AMOS on MCS

One exercise agreed in class [optional, dependent upon department]

• Barbara Bryne (2001). Structural Equation Modelling With AMOS: Basic Concepts, Applications, and Programming. Lawrence Erlbraum Associates, Mahwah, NJ
• Kline, Rex B. (2005), Principles and Practice of Structural Equation Modelling, The Guildford Press, New York

• To gain maximum benefits from the course it is important that students do not see this course in isolation from the other MPhil courses or research training they are taking.
• Responsibility lies with each student to consider the potential for their own research using methods common in fields of the social sciences that may seem remote. Ideally this task will be facilitated by integration of the SSRMC with discipline-specific courses in their departments and through reading and discussion.

Four sessions of two hours each.

Once a week for four weeks.