Factor Analysis

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.

This module introduces the statistical techniques of Exploratory and Confirmatory Factor Analyses. Exploratory Factor Analysis (EFA) is used to uncover the latent structure (dimensions) of a set of variables. It reduces the attribute space from a larger number of variables to a smaller number of factors. Confirmatory Factor Analysis (CFA) examines whether collected data correspond to a model of what the data are meant to measure. STATA will be introduced as a powerful tool to conduct confirmatory factor analysis. A brief introduction will be given to confirmatory factor analysis and structural equation modelling.

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

• Students expected to be familiar with basic statistical concepts such as variance, correlation and regression
• Course also assumes familiarity with using the essential features of Stata
• You must have joined the SSRMC Camtools site

Number of sessions: 4

• Session 1: Exploratory Factor Analysis Introduction
• Session 2: Factor Analysis Applications
• Session 3: CFA and Path Analysis with STATA
• Session 4: Introduction to SEM and programming

• To learn and understand confirmatory factor analysis and regression analysis

Presentations, demonstrations and practicals

Stata on MCS

One practical exercise [optional, dependent upon department]

• Bartholomew, D. J., Steele, F., & Moustaki, I. (2008). Analysis of Multivariate Social Science Data (2nd ed ed.). New York, NY: Chapman & Hall/CRC Press.
• Long, J. S. (1983). Confirmatory Factor Analysis: A Preface to LISREL: SAGE Publications.
• Kim, J. O., & Mueller, C. W. (1978). Factor Analysis: Statistical Methods and Practical Issues: SAGE Publications.
• LP., S., Hamilton, L. C., & Corporation, S. (2011). Stata Structural Equation Modeling Reference Manual-Release 12: StataCorp LP.

In addition, there are chapters on Exploratory and Confirmatory Factor Analysis in the Electronic Statistics Textbook (EST): http://www.statsoft.com/textbook/stathome.html

• 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.