Type of Credit: Elective
Credit(s)
Number of Students
This course familiarizes students with several flagship large‑scale international survey data, including the World Values Survey (WVS), East Asian Social Survey (EASS), International Social Survey Programme (ISSP), Programme for International Student Assessment (PISA), and the WHO Study on Global AGEing and Adult Health (SAGE). Through a combination of lectures, hands‑on exercises, a research proposal, and a final empirical project, students will master cross‑national survey design, data cleaning and documentation, weighting, measurement validity checks, cross‑country dataset integration, data analysis and hypothesis testing, and concise written and oral reporting. Demonstrations in class will use R. However, students may complete assignments with any statistical software (e.g., Python, Stata, SAS, SPSS, etc.). There are no formal prerequisites for this course. However, prior completion of (or concurrent enrolment in) an introductory statistics or quantitative research‐methods course is strongly recommended.
能力項目說明
By the end of the course, students will be able to:
Week |
Topic |
Teaching Activities and Homework |
1 |
Introduction: Why international surveys? |
|
2 |
World Values Survey (WVS), sampling & data management: How do we access, understand, and use an international survey? |
|
3 |
East Asian Social Survey (EASS), survey method, & localizing international surveys: How do countries implement international surveys in local settings? |
|
4 |
International Social Survey Programme (ISSP), non‑response & missing data: Why should we care about those who did not respond? |
Problem Set 1 due Oct. 1 |
5 |
Programme for International Student Assessment (PISA), measurement, reliability & validity: How do we measure (operationalize) concepts? |
|
6 |
Study on global AGEing and adult health (SAGE), Longitudinal surveys, and merging datasets: When and how do we combine (merge and append) different datasets? |
Paper Reading Note 1 due Oct. 15 |
7 |
Country‑level data, and aggregated analysis: How can we examine the influence of country‑level characteristics? |
|
8 |
Comparative studies, and weighting: How do we conduct an international comparative study? |
Problem Set 2 due Oct. 29 |
9 |
Literature review, hypothesis development, and academic writing |
|
10 |
Proposal workshop |
Research Proposal due Nov. 12 |
11 |
Review of introductory statistics |
|
12 |
Advanced statistics: standardized coefficients, mediation, moderation |
Paper Reading Note 2 due Nov. 26 |
13 |
Cross‑country comparison: subgroup & clustered data; What special considerations and techniques apply to international comparative studies? |
|
14 |
Cross‑country comparison: fixed effects & diff‑in‑diff; How can we use other countries as a control group? |
Problem Set 3 due Dec. 10 |
15 |
Student presentations (I) |
|
16 |
Student presentations (II) |
Final Paper due Dec. 24 |
Weekly Topic and Readings
Week 1 (Sep. 4) Introduction to the Course
Week 2 (Sep. 11) World Values Survey (WVS), Sampling, and Data Management
Week 3 (Sep. 18) East Asian Social Survey (EASS), Survey Method, Localizing International Survey
Week 4 (Sep. 25) International Social Survey Programme (ISSP), Nonresponse Bias, Missing Values
Week 5 (Oct. 2) Programme for International Student Assessment (PISA), Variables Measurement, Reliability, and Validity
Week 6 (Oct. 9) Study on global AGEing and adult health (SAGE), Longitudinal Survey, Combining Datasets
Week 7 (Oct. 16) Country Level Data, Aggregating Analysis
Week 8 (Oct. 23) International Comparative Study and Weighting
Week 9 (Oct. 30) Literature Review, Hypotheses Development, and Academic Writing
Week 10 (Nov. 6) Proposal Workshop
Week 11 (Nov. 13) Review: Introductory Level Statistics
Week 12 (Nov. 20) Advanced Statistics: Standardized Coefficients, Mediation, and Moderation
Week 13 (Nov. 27) Cross-Country Comparison: Subgroup Analysis, Cluster Data
Week 14 (Dec. 4) Cross-Country Comparison: Fixed Effect, Difference-in-Differences
Week 15 (Dec. 11) Presentation
Week 16 (Dec. 18) Presentation
Late Submission Policy: Written works are due at 23:59 on the stated date. Problem sets cannot be submitted late. For paper-reading notes and research project, late submissions will lose 10 percent of the available points for each 24-hour period past the deadline, unless the instructor has approved an extension in advance or grants a waiver afterward due to an unforeseen emergency. An unexcused absence from a scheduled presentation without prior arrangement earns a grade of zero for that component.
Guidelines for the Use of Generative AI Tools in the Classroom
Textbook:
All other assigned readings are available from the course website.