Quantitative Research IV: Confirmatory factor analysis and structural equation models

Schedule and location

Monday February 27th – Tueday February 28th  

University of Jyväskylä, Jyväskylä, Agora building (visiting address: Mattilanniemi 2), room Lea Pulkkisen sali (4th floor, mornings) and computer class Ag B112.1 (afternoons).



Registration is open January 20th - February 20th.


Dr. Mikko Rönkkö, University of Jyväskylä, Finland.


Dr. Mikko Rönkkö, University of Jyväskylä, Finland.


Many researchers use quantitative research designs and statistical analysis tools without sufficient understanding on what these techniques are based on. This course is a part of a series of six courses where the goal is to develop an understanding of how multivariate statistical methods are used in information systems research and how results are usually presented in journal articles. The main goal of the course is to provide a foundation that enables independent self-study of quantitative research methods. Rather than addressing simply how the methods are used, we focus on why certain methods are used and how and why these methods work.

The course is designed for both those interested in just reading and understanding research done with statistical methods and for those who already use or plan to use statistical research methods in their own work.

During the course series we will go through six empirical papers published in leading IS and management journals, and analyze how these papers were done. The methods and research designs used in these papers cover a majority of methods and designs used in these journals. If you master all the methods and techniques presented during the course, you would be ideally capable to publish in these journals – if you have already a new theoretical insight and access to appropriate data.

In this fourth course, we address confirmatory factor analysis and structural equation modeling. Structural equation modeling is a family of techniques for estimating and testing of systems of equations with more than one dependent variable. Perhaps the simplest possible such model is a simple mediation model, where the association between two observed variables goes through a third observed variable. This kind of models that contain only observed variables are called path analysis models. Confirmatory factor analysis model is a second commonly used type of structural equation model. These models are typically used for testing measurement theory in the case where we have multiple concept each measured with multiple indicators. The third model type that we cover during the course is the structural regression model, which is a combination of a path model and a confirmatory factor analysis model. This kinds of models are frequently used as the main data analysis technique in IS research.

During the course we address the basics of specification and estimation of these three kinds of models discussing issues such as identification, model testing, diagnostics, and interpretation of results. You can complete the course using either Stata, R, or SPSS AMOS.

The course has a pre-class readings package and a pre-class assignment that must be returned before the course and a post-class report that must be returned after the course. You should reserve at least two days for the pre-class assignment and at least a day for the post-class report. The course assumes that the participants have a basic understanding of regression models and factor analysis. You can participate the course even if you did not participate on the previous courses.

Detailed Program


Day 1 – Morning

Course introduction

Path analysis models

  • Simple mediation model
  • Estimation and testing
  • Recursive and non-recursive models

Confirmatory factor analysis

  • The rationale for confirmatory factor analysis
  • Identification
  • Estimation
  • Admissibility
  • Introduction to model testing and diagnostics


Day 1 - Afternoon (computer class)

Path analysis with Excel

Introducing the data-analysis assignment

Confirmatory factor analysis models

  • Specification, identification, and estimation
  • Model testing and diagnostics

Day 2 – Morning

Structural regression models

  • Specification, identification, and estimation
  • Model testing and diagnostics

Modeling strategies

  • Two-step modeling
  • Nested model comparisons
  • Modification indices and specification search

The role of assumption in structural equation models

Current issues and debates in structural equation modeling

  • Model testing: chi2 vs. descriptive and alternative fit indices
  • The PLS problem
  • Formative and reflective measurement models

Day 2 - Afternoon (computer class)

Structural regression models

  • Specification, identification, and esetimation
  • Model testing and diagnostics
  • Nested model comparisons
  • What to do when a model does not converge or produces inadmissible results

Working on the data-analysis assignment and post-class report

Credit points

Doctoral students participating in the seminar can obtain 2 credit points. This requires participating on both days and returning the pre-class assignment and post-class report.

Registration fee

This seminar is free-of-charge for Inforte.fi member organization's staff and their PhD students. For others the participation fee is 400 €. The participation fee includes access to the event and the event materials. Lunch and dinner are not included.