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Summer Course: Theory testing with structural equation modelling

Projects Topo

The summer course in "Theory testing with structural equation modelling" will be held from June 20th to 24th, 2022 (from 2 p.m. to 7 p.m.), in person and online.

This course will provide an introduction to structural equation modelling (SEM), including the study of methods based on covariance (traditional SEM) as well as the Partial Least Squares (PLS-SEM) method. The course will also include an approach to confirmatory factor analysis.

The applications will be supported by both covariance-based SEM and PLS based software. It is designed for non-experts in SEM and it will be focused on the understanding of SEM methodologies and their application as a research tool in social sciences.

The main goal of this course is to provide professionals, researchers and Master or Doctorate students with the modelling and data analysis tools necessary to test theories in social sciences.

This course will be taught in English.

Expected Results

After completing the course, participants should be familiar with the various steps associated with the specification, identification, estimation, evaluation and modification of structural equation models needed to test theories in social sciences.

Participants should also be able to select the estimation methods that are most appropriate in the context in which they work, know the application requirements of each method and make the most appropriate decisions at every stage of modelling. Finally, participants should be able to organize and present the produced results and to write the results section of a report or a scientific paper.


  1. Introduction and motivation to use SEM models
  2. Representation of a structural equation model
  3. Theory testing with SEM models
  4. Confirmatory Factor Analysis
  5. SEM modelling based on covariance
    1. Specification
    2. Identification
    3. Estimation
    4. Evaluation
    5. Modification
  6. SEM modelling based on PLS
    1. Specification and evaluation of the measurement model
    2. Specification and evaluation of the structural model
  7. How to write the results section of a project or scientific paper
  8. Examples and exercises



  • Lehlin, J. C. (1987). Latent variables models, Hillsdale, NJ: Lawrence Erlbaum associates.
  • Bollen, K.A. (1989). Structural Equations with Latent Variables. New York: John Wiley & Sons.
  • Hair, Hult, Ringle (2014). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). SAGE Publications.
  • Henseler, J.; Hubona, G.; Ray, P. (2015). Using PLS path modeling in new technology research: updated guidelines, Industrial Management and Data Systems, vol. 116, No. 1.


Pedro Simões Coelho

Pedro Simões Coelho is presently Full Professor and President of the Scientific Board of the NOVA Information Management School (NOVA IMS) of Universidade Nova de Lisboa. He is also researcher in the Information Management Research Center (MagIC) of NOVA University. He is presently senior expert near the European Commission for the area of statistical methods and sampling techniques.

He is member of the board of the European Master of Official Statistics (EMOS), member of the Ischools accreditation committee, member of the Portuguese Health Technologies Commission and head of information and statistics in NOVA Clinical Research Unit (NOVA CRU). He is former President of the General Assembly of the Portuguese Association for Classification and Data Analysis (CLAD), former member of the Portuguese High Council for Statistics (CSE) and President of the Fiscal Board of the European Center of Statistics for the Developing Countries (CESD-Lisboa).

Pedro S. Coelho has “aggregation” (post-doctoral degree) in Statistics (NOVA University), PhD in Statistics (NOVA University), MSc in Statistics and Information Management and a graduation in Systems Engineering. He has been lecturer of near 30 graduate and undergraduate courses, including Structural Equation Modeling, Research Methodologies, Sampling, Survey Methodology, Marketing Research, Data Collection Methodologies and Data Analysis.

He is author of about 200 studies and projects, resulting in more than 500 research reports. He is also author of more than 100 refereed publications. He has presented near 100 seminars, invited conferences and oral presentations in scientific conferences.

Pedro S. Coelho has been consultant and trainer for several organizations, namely for the European Commission, Eurostat, the Portuguese Statistical Office, the Portuguese Central Bank and several National Statistical Offices around the world. For these institutions has been developing methodologies and offering training in data analysis techniques.