Jeromy Anglim's Blog: Psychology and Statistics


Thursday, October 10, 2013

Tutorials, Answers, and Data Files for Multivariate Research Methods Course using SPSS and Amos

I recently developed a set of tutorials for teaching research methods using SPSS and Amos to I/O psychology students. I thought they might be useful for other instructors or people learning intermediate multivariate research methods to social and behavioural science students. Thus, I have made the resources available as a downloadable repository.

Each tutorial includes a set of exercises, data, and extensive answers. A particular emphasis is on using syntax, reproducible workflow in SPSS, managing metadata, and scale construction.

It contains six tutorial exercises.

  • Introduction to data analysis
  • Correlation and regression
  • Group differences
  • Moderators and mediators
  • Exploratory factor analysis
  • Confirmatory factor analysis

For example, here is the tutorial on confirmatory factor analysis with Amos in docx format. The repository also includes related data files.

GITHUB Repository Address: https://github.com/jeromyanglim/spss-research-methods-tutorials

Each exercise includes several folders

  • Instructions: This folder includes one or more Word documents with the exercise and answers. These files should be your starting point for getting an understanding of the tutorials.
  • data: This folder includes raw data and meta data used in the tutorial exercises. There are often raw csv files as well as various SPSS sav files. The exercises are designed to teach students how to import and process csv files in SPSS.
  • output: These folders often include a copy of much of the SPSS output in PDF form as well as some syntax files.

To use the repository it is recommended that you download the ZIP file.

Earlier versions of the corresponding lectures can basically be found in the teaching resources section of my website under multivariate methods.

Author: Dr Jeromy Anglim, Deakin University

Licence: Tutorial exercises are given a creative commons licence CC BY 3.0. Raw data files and data descriptions retain whatever licence they had previously.