{"id":10267,"date":"2021-10-14T10:52:33","date_gmt":"2021-10-14T01:52:33","guid":{"rendered":"https:\/\/www.waseda.jp\/inst\/sgu\/?p=10267"},"modified":"2021-10-14T10:52:33","modified_gmt":"2021-10-14T01:52:33","slug":"essex-summer-school-online-2021-course-report","status":"publish","type":"post","link":"https:\/\/www.waseda.jp\/inst\/sgu\/news-en\/2021\/10\/14\/10267\/","title":{"rendered":"Essex Summer School Online 2021 Course Report"},"content":{"rendered":"

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).<\/p>\n

Held online this year, seven students participated in each selected course.\u00a0 They worked diligently to solve their respective problems, and through the two-week (35 hours) intensive course,\u00a0 they successfully obtained their intended results and clues for their future research and thesis.<\/p>\n

Course Report:\u00a02N Confirmatory Factor Analysis and Structural Equation Modelling<\/span><\/span>\u00a0<\/span><\/span><\/span><\/h2>\n

\"\"Name: NAKASATO Lauren Noelani<\/span><\/span>\u00a0<\/span><\/h2>\n

Graduate School of Asia-Pacific Studies<\/span><\/span>\u00a0Doctoral Student\u00a0<\/span><\/p>\n

\u00a0 \u00a0Research Theme:\u00a0Empirical Examination of the Impact of Study Abroad<\/span><\/span> and Internationalization at Home on Global Citizenship Outcomes<\/span><\/span><\/p>\n

Prior to this course\u00a0I\u00a0had\u00a0tried to\u00a0learn\u00a0CFA and SEM\u00a0on my own\u00a0as\u00a0my research deals with the\u00a0complex\u00a0latent construct\u00a0\u201cglobal citizenship\u201d.\u00a0However,\u00a0I was not able to determine whether the analysis was\u00a0possible with my specific data set and research question. Therefore,\u00a0I had the following questions going into this course:<\/p>\n

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  1. \n
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    Above: The professor explains a recursive path model
    Below: Discussion about a classmate’s proposed SEM model during the project presentations<\/p><\/div>\n

    Is CFA\/SEM possible\u00a0with ordinal (Likert scale) data? If so, how can it be done?<\/li>\n

  2. Is CFA\/SEM possible\u00a0without having used an established measurement tool to collect the data (as my data is secondary data)? If so, how can it be done?<\/li>\n
  3. How strong does the theoretical basis for the model need to be to qualify for CFA (as opposed to EFA)?<\/li>\n<\/ol>\n

    Through the course I discovered that CFA\/SEM is certainly possible with Likert scale data by using the weighted least squares estimator,\u00a0but due to the complexity of interpreting the results I may be able to treat my data as continuous instead. Regarding\u00a02), 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\u00a0use. Regarding 3), I found that the theoretical basis for the model\u00a0has to\u00a0be quite strong, and that\u00a0using an established theory which has been verified empirically will likely produce better fitting models. In my case,\u00a0I need to strengthen the theoretical basis for my\u00a0model.<\/p>\n

    Aside from these specific\u00a0goals, the course also\u00a0helped me to\u00a0understand the theoretical foundations\u00a0and practical applications\u00a0of CFA and SEM.\u00a0Each\u00a0four-hour\u00a0class\u00a0was comprised of a theoretical and practical\u00a0session.\u00a0The theoretical\u00a0session consisted of lecture\u00a0and\u00a0periodic tasks and transfer questions. The tasks\u00a0allowed\u00a0me to grasp the content as it\u00a0forced\u00a0me\u00a0to immediately use the concepts\u00a0I\u00a0had learned. The\u00a0transfer questions helped\u00a0me to transfer the concepts to my own research as they\u00a0asked\u00a0how\u00a0we\u00a0plan to use the analyses in our own research.\u00a0In the practical session I\u00a0ran\u00a0analyses in real time using\u00a0the\u00a0application\u00a0Mplus.\u00a0I\u00a0learned the\u00a0Mplus\u00a0syntax which I immediately applied\u00a0to my own research and data.<\/p>\n

    The course culminated\u00a0in a final presentation in which\u00a0I\u00a0shared\u00a0progress on\u00a0my\u00a0CFA\/SEM\u00a0using my\u00a0own data.\u00a0I was able to\u00a0receive guidance and feedback from classmates and instructors\u00a0about the viability of my model and issues I was facing in the analysis. I was also able to\u00a0I\u00a0take\u00a0advantage of an individual consultation with\u00a0the\u00a0main\u00a0professor\u00a0in which he evaluated my model and gave me advice for proceeding with my analysis.\u00a0While I\u00a0did not\u00a0complete the\u00a0entire\u00a0analysis, I was able to\u00a0present and receive feedback on my model and preliminary steps of the analysis.\u00a0I can now confidently proceed with\u00a0model modifications.\u00a0I hope to not only use the analysis in my PhD dissertation but also in a future publication.<\/p>\n

     <\/p>\n

    Comments after the course:<\/h3>\n

    “I am incredibly grateful for this tremendous opportunity to improve my data analysis skills.\u00a0<\/span>After struggling with\u00a0<\/span>self-study<\/span>\u00a0I\u00a0<\/span>was trying to find a tutor<\/span>\u00a0or online course<\/span>\u00a0but<\/span>\u00a0there were few options in this specific area of expertise and what did exist was too expensive for me.\u00a0<\/span>When this opportunity\u00a0<\/span>arose<\/span>\u00a0it was like a dream come true.<\/span><\/span>\u00a0<\/span><\/span>Not only did I\u00a0<\/span>achieve the goals\u00a0<\/span>I had set prior to the course,\u00a0<\/span>I<\/span>\u00a0<\/span>was also able to experience an online class run in a different style than I am used to and\u00a0<\/span>me<\/span>e<\/span>t other students and researchers from\u00a0<\/span>around the world<\/span><\/span>.\u00a0<\/span><\/span>I am grateful to <\/span>Waseda<\/span>\u00a0University and the SGU Office for providing this amazing opportunity.<\/span>\u00a0Thank you<\/span>\u00a0so very much.”<\/span><\/span>\u00a0<\/span><\/p>\n

    The course reports and feedback from other students can be accessed here<\/a>.<\/p>\n

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    Participants’ feedback 2021<\/a><\/h2>\n

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    (Labels starting from left) Blue: Not good at all, Red: Not very good, Orange: Average, Green: Above average, Purple: Well above average<\/p><\/div>\n

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    (Labels starting from left) Blue: Strongly disagree, Red: Disagree, Orange: Neither agree nor disagree, Green: Agree, Purple: Strongly agree<\/p><\/div>\n

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    (Labels starting from left) Blue: Strongly disagree, Red: Disagree, Orange: Neither agree nor disagree, Green: Agree, Purple: Strongly agree<\/p><\/div>\n

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    (Labels starting from left) Blue: No, Red: I don’t know, Orange: Yes, Green: Yes, if a subsidy is offered.<\/p><\/div>\n