Top Global University Project: Waseda Goes Global - A Plan to Build a Worldwide Academic Network That Is Open, Dynamic and DiverseWaseda University


Essex Summer School Online 2021 Course Report

The Center for Positive/Empirical Analysis of Political Economy (TGU Project) supports Waseda graduate students in order to refine the higher international sense and analyzing ability in social science by subsidizing their participation fee for Essex Summer School in Social Science Data Analysis (SSDA).

Held online this year, seven students participated in each selected course.  They worked diligently to solve their respective problems, and through the two-week (35 hours) intensive course,  they successfully obtained their intended results and clues for their future research and thesis.

Course Report: 2N Confirmatory Factor Analysis and Structural Equation Modelling 

Name: NAKASATO Lauren Noelani 

Graduate School of Asia-Pacific Studies Doctoral Student 

   Research Theme: Empirical Examination of the Impact of Study Abroad and Internationalization at Home on Global Citizenship Outcomes

Prior to this course I had tried to learn CFA and SEM on my own as my research deals with the complex latent construct “global citizenship”. However, I was not able to determine whether the analysis was possible with my specific data set and research question. Therefore, I had the following questions going into this course:

  1. Above: The professor explains a recursive path model
    Below: Discussion about a classmate’s proposed SEM model during the project presentations

    Is CFA/SEM possible with ordinal (Likert scale) data? If so, how can it be done?

  2. Is CFA/SEM possible without having used an established measurement tool to collect the data (as my data is secondary data)? If so, how can it be done?
  3. How strong does the theoretical basis for the model need to be to qualify for CFA (as opposed to EFA)?

Through the course I discovered that CFA/SEM is certainly possible with Likert scale data by using the weighted least squares estimator, but due to the complexity of interpreting the results I may be able to treat my data as continuous instead. Regarding 2), it is certainly possible but would require that an exploratory factor analysis (EFA) be conducted prior the CFA/SEM to validate the items that I want to use. Regarding 3), I found that the theoretical basis for the model has to be quite strong, and that using an established theory which has been verified empirically will likely produce better fitting models. In my case, I need to strengthen the theoretical basis for my model.

Aside from these specific goals, the course also helped me to understand the theoretical foundations and practical applications of CFA and SEM. Each four-hour class was comprised of a theoretical and practical session. The theoretical session consisted of lecture and periodic tasks and transfer questions. The tasks allowed me to grasp the content as it forced me to immediately use the concepts I had learned. The transfer questions helped me to transfer the concepts to my own research as they asked how we plan to use the analyses in our own research. In the practical session I ran analyses in real time using the application Mplus. I learned the Mplus syntax which I immediately applied to my own research and data.

The course culminated in a final presentation in which I shared progress on my CFA/SEM using my own data. I was able to receive guidance and feedback from classmates and instructors about the viability of my model and issues I was facing in the analysis. I was also able to I take advantage of an individual consultation with the main professor in which he evaluated my model and gave me advice for proceeding with my analysis. While I did not complete the entire analysis, I was able to present and receive feedback on my model and preliminary steps of the analysis. I can now confidently proceed with model modifications. I hope to not only use the analysis in my PhD dissertation but also in a future publication.


Comments after the course:

“I am incredibly grateful for this tremendous opportunity to improve my data analysis skills. After struggling with self-study I was trying to find a tutor or online course but there were few options in this specific area of expertise and what did exist was too expensive for me. When this opportunity arose it was like a dream come true. Not only did I achieve the goals I had set prior to the course, I was also able to experience an online class run in a different style than I am used to and meet other students and researchers from around the worldI am grateful to Waseda University and the SGU Office for providing this amazing opportunity. Thank you so very much.” 

The course reports and feedback from other students can be accessed here.

Participants’ feedback 2021



(Labels starting from left) Blue: Not good at all, Red: Not very good, Orange: Average, Green: Above average, Purple: Well above average


(Labels starting from left) Blue: Strongly disagree, Red: Disagree, Orange: Neither agree nor disagree, Green: Agree, Purple: Strongly agree


(Labels starting from left) Blue: Strongly disagree, Red: Disagree, Orange: Neither agree nor disagree, Green: Agree, Purple: Strongly agree


(Labels starting from left) Blue: No, Red: I don’t know, Orange: Yes, Green: Yes, if a subsidy is offered.

  • For those interested in the course report for 2020, please access the link below:

14 Waseda graduate students attend Essex Summer School online 2020 – Top Global University Project: Waseda Goes Global

Page Top
WASEDA University

The Waseda University official website
<<>> doesn't support your system.

Please update to the newest version of your browser and try again.


Suporrted Browser