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Instructor-led course

Provided by: Joint Schools' Social Sciences


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Module 8: Factor Analysis and SEM
Prerequisites


Description

Introduction to statistical techniques of Exploratory and Confirmation Factor Analyss. EFA is used to uncover the latent structure of a set of variables. CFA examines whether collected date correspond to a model of what the data are meant to measure. AMOS will be introduced as a powerful tool to conduct confirmatory factor analysis.

Target audience

Mphil Students from participating departments taking the Social Science Research Methods Course as part of their research degree

Prerequisites

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 SPSS.

Topics covered
  • Session 1: Exploratory Factor Analysis Introduction
  • Session 2: Factor Analysis Applications
  • Session 3: Introduction to SEM and AMOS programming.
  • Session 4: CFA Path Analysis with AMOS
Objectives
  • The objective is to introduce students to statistical techniques of Exploratory and Confirmatory Factor Analyses.
Aims
  • To learn and understand confirmatory factor analysis and regression analysis combined in structural equation modelling.
Format

Presentations, demonstrations and practicals

Taught using

SPSS v. 16 on PWF Windows

Assessment

Three exercises

Textbook(s)

Field,A. Discovering Statistics Using SPSS. London:Sage. Bryne, B (2001) Structural Equation Modelling with AMOS: Basic Concepts, Applications and Programming. Mahwah, NJ: Lawrence Erlbraum.

Students also expected to have read: http://www.statsoft.com/textbook/stathome.html chapters on Exploratory and Confirmatory Factor Analysis.

Notes
  • To gain the 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.
Duration

Four sessions to two hours

Frequency

Four times in Lent term

Theme
Advanced Statistics

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