Weekly Topic and Readings

Week 1 (Sep. 4) Introduction to the Course

• What is a survey? What are international surveys? Why do we need them?

Week 2 (Sep. 11) World Values Survey (WVS), Sampling, and Data Management

• How do we access, understand, and use an international survey?


• Readings
  
  
  
  • Sheppard, Ch 7. Sampling Techniques. pp.155–183.
  
  
  • Website of the World Value Survey (WVS) https://www.worldvaluessurvey.org/WVSContents.jsp (Read Who We Are and What We Do)
  
  
  
  


• Resources
  
  
  
  • Jenkins-Smith et al. Ch 17. Basic R
  
  
  • Jenkins-Smith et al. Ch 3. Exploring and Visualizing Data
  
  
  
  

Week 3 (Sep. 18) East Asian Social Survey (EASS), Survey Method, Localizing International Survey

• How do countries implement international surveys in local settings?

• Readings
  
  
  
  
  • Sheppard, Ch 8. Data Collection Methods: Survey Research. pp.185–219.
  
  
  • Website of the East Asian Social Survey (EASS). https://www.eassda.org/index.php (Read AboutEASSand Participating Institutions)
  
  
  
  


• Optional Readings
  
  
  
  • Iwai, N., Mo, T., Kim, J., Wu, C. I., & Wang, W. (2024). Harmonization in the East Asian Social Survey. In Tomescu-Dubrow, I., Wolf, C., Slomczynski, K. M., & Jenkins, J. C. (Eds.). Survey Data Harmonization in the Social Sciences. John Wiley & Sons. pp. 107–124.
  
  
  • Behr, D., & Shishido, K. (2016). The translation of measurement instruments for cross-cultural surveys. In Wolf, C., Fu, Y. C., Smith, T., & Joye, D. (Eds). The SAGE handbook of survey methodology. Sage Publications. pp. 269–287.
  
  
  • Stone, L., & Campbell, J. G. (1984). The use and misuse of surveys in international development: an experiment from Nepal. Human Organization, 43(1), 27–37.
  
  
  
  

Week 4 (Sep. 25) International Social Survey Programme (ISSP), Nonresponse Bias, Missing Values

• Why should we care about those who did not respond?


• Readings
  
  
  
  • Website of International Social Survey Programme (ISSP) https://issp.org/survey-topics/ (Read About ISSP and Survey Topics)
  
  
  • Rybak, A. (2023). Survey mode and nonresponse bias: A meta-analysis based on the data from the International Social Survey Programme waves 1996–2018 and the European Social Survey rounds 1 to 9. PLoS One, 18(3), e0283092.
  
  
  • Acock, A. C. (2005). Working with missing values. Journal of Marriage and Family, 67(4), 1012–1028.
  
  
  
  


• Assignment
  
  
  
  • Problem Set 1. Due Oct. 1.
  
  
  
  

Week 5 (Oct. 2) Programme for International Student Assessment (PISA), Variables Measurement, Reliability, and Validity

• How do we measure (operationalize) concepts?


• Readings
  
  
  
  • Sheppard, Ch 4. Measurement and Units of Analysis. pp.79–106.
  
  
  • Lee, J. (2009). Universals and specifics of math self-concept, math self-efficacy, and math anxiety across 41 PISA 2003 participating countries. Learning and Individual Differences, 19(3), 355–365.
  
  
  • Website of Programme for International Student Assessment (PISA) https://www.oecd.org/en/about/programmes/pisa.html (Read About and Participation)
  
  
  
  


• Resources
  
  
  
  • Zhang & Kwon. Factor Analysis. R Programming for Psychometrics. https://bookdown.org/sz_psyc490/r4psychometics/factor-analysis.html
  
  
  • Zhang & Kwon. Reliability: Coefficient α. R Programming for Psychometrics. https://bookdown.org/sz_psyc490/r4psychometics/reliability.html#coefficient-alpha
  
  
  
  

Week 6 (Oct. 9) Study on global AGEing and adult health (SAGE), Longitudinal Survey, Combining Datasets

• When and how do we combine (merge and append) different datasets?


• Readings
  
  
  
  • Website of Study on global AGEing and adult health (SAGE). https://www.who.int/data/data-collection-tools/study-on-global-ageing-and-adult-health/sage-waves
  
  
  • Kowal, P., Chatterji, S., Naidoo, N., Biritwum, R., Fan, W., Lopez Ridaura, R., ... & SAGE collaborators. (2012). Data resource profile: the World Health Organization Study on global AGEing and adult health (SAGE). International Journal of Epidemiology, 41(6), 1639–1649.
  
  
  
  


• Resources
  
  
  
  • Merging. Data Wrangling with R. University of Wisconsin–Madison. https://sscc.wisc.edu/sscc/pubs/dwr/merge-base.html
  
  
  
  


• Optional Readings
  
  
  
  • Alderman, H., Behrman, J. R., Kohler, H. P., Maluccio, J. A., & Watkins, S. C. (2001). Attrition in longitudinal household survey data: some tests for three developing-country samples. Demographic Research, 5, 79–124.
  
  
  
  


• Assignment:
  
  
  
  • Paper Reading Note 1. Due Oct. 15.
  
  
  
  

Week 7 (Oct. 16) Country Level Data, Aggregating Analysis

• How can we examine the influence of country‑level characteristics such as political institutions, culture, or economic development?


• Readings:
  
  
  
  • Leigh, A., & Wolfers, J. (2006). Happiness and the human development index: Australia is not a paradox. Australian Economic Review, 39(2), 176–184.
  
  
  • Yodanis, C. (2005). Divorce culture and marital gender equality: A cross-national study. Gender & Society, 19(5), 644–659.
  
  
  
  


• Resources
  
  
  
  • Human Development Index (HDI). https://hdr.undp.org/data-center/human-development-index#/indicies/HDI
  
  
  • Corruption Perceptions Index (CPI). https://www.transparency.org/en/cpi/2024
  
  
  • Undata. https://data.un.org
  
  
  • OECD data: https://data-explorer.oecd.org
  
  
  • Aggregating. Data Wrangling with R. University of Wisconsin–Madison. https://sscc.wisc.edu/sscc/pubs/dwr/aggregate-base.html
  
  
  
  

Week 8 (Oct. 23) International Comparative Study and Weighting

• How do we conduct an international comparative study when samples are non‑representative?


• Readings
  
  
  
  • Ariely, G., & Davidov, E. (2011). Can we rate public support for democracy in a comparable way? Cross-national equivalence of democratic attitudes in the World Value Survey. Social Indicators Research, 104, 271-286. (Just read sections 1, 2, & 5)
  
  
  • Silver, B. D., & Dowley, K. M. (2000). Measuring political culture in multiethnic societies: Reaggregating the World Values Survey. Comparative Political Studies, 33(4), 517-550.
  
  
  
  


• Resources
  
  
  
  • Federico Vegetti. Survey Weights with R. https://federicovegetti.github.io/teaching/heidelberg_2018/lab/sst_lab_day2.html
  
  
  
  


• Assignment:
  
  
  
  • Problem Set 2. Due Oct. 29.
  
  
  
  

Week 9 (Oct. 30) Literature Review, Hypotheses Development, and Academic Writing

• How do we develop research questions and hypotheses and use literature to justify them?


• Readings
  
  
  
  • Sheppard, Ch3. Developing a Research Question. pp.55–76.
  
  
  • Sheppard, Ch 5. The Literature Review. pp.109–127.
  
  
  • Avoiding Plagiarism. Harvard Guide to Using Sources. https://usingsources.fas.harvard.edu/sites/g/files/omnuum4606/
    
    files/sources/files/avoiding_plagiarism.pdf
  
  
  
  

Week 10 (Nov. 6) Proposal Workshop

• Readings
  
  
  
  
  • Sheppard, Ch 14. The Research Proposal. pp.349–361.
  
  
  
  


• Assignment
  
  
  
  • Research Proposal. Due Nov. 12.
  
  
  
  

Week 11 (Nov. 13) Review: Introductory Level Statistics

• Summary statistics, t-test, chi-square, ANOVA, correlation, regression


• Readings
  
  
  
  • Jenkins-Smith et al. (Skim the section titles, skip the mathematical parts, focus on the concepts and application). You can also choose to review the statistical textbook used in your other course.
    
    
    
    • Ch 5. Inference.
    
    
    • Ch 6. Association of Variables.
    
    
    • Section II. Simple Regression.
    
    
    • Section III. Multiple Regression.
    
    
    • Section IV Generalized Linear Models.
    
    
    
    
  
  
  
  

Week 12 (Nov. 20) Advanced Statistics: Standardized Coefficients, Mediation, and Moderation

• Readings
  
  
  
  
  • Yamashita, T., Bardo, A. R., & Liu, D. (2016). Are East Asians happy to work more or less? Associations between working hours, relative income and happiness in China, Japan, South Korea and Taiwan. Asian Journal of Social Psychology, 19(3), 264-274. [Just read from the beginning to the Research question and hypotheses section and Figure 1.]
  
  
  • Lim, H. E., Shaw, D., Liao, P. S., & Duan, H. (2020). The effects of income on happiness in East and South Asia: Societal values matter?. Journal of Happiness Studies, 21, 391–415. [Just read the Introduction and Data and Methodology Sections]
  
  
  
  


• Assignment
  
  
  
  • Paper Reading Note 2. Due Nov. 26.
  
  
  
  

Week 13 (Nov. 27) Cross-Country Comparison: Subgroup Analysis, Cluster Data

• What special considerations and techniques apply to international comparative studies?


• Readings        
  
  
  
  • Babones, S. J. (2010). Trade globalization, economic development and the importance of education-as-knowledge. Journal of Sociology, 46(1), 45-61.
  
  
  • Grabau, L., Galand, B., Lafontaine, D., Lavonen, J., Ólafsson, R. F., Trudel, L., & Yoon, S. (2024, July). What is the association between schoolwork-related anxiety and science literacy proficiency? A comparison between Southeast Asia and Northwest Europe. Frontiers in Education, 9, 1414423.
  
  
  
  

Week 14 (Dec. 4) Cross-Country Comparison: Fixed Effect, Difference-in-Differences

• How can we use other countries as a control group?


• Readings
  
  
  
  • Kikuta, K., & Hanayama, M. (2025). The Nobel Peace Prize Increased the Global Support for Women’s Organizations: Prize and Praise in International Relations. Perspectives on Politics, 23(2). 494–510.
  
  
  • Hanushek, E. A., & Wößmann, L. (2006). Does educational tracking affect performance and inequality? Differences‐in‐differences evidence across countries. The Economic Journal, 116(510), C63–C76.
  
  
  
  


• Assignment
  
  
  
  • Problem Set 3. Due Dec. 10.
  
  
  
  

Week 15 (Dec. 11) Presentation

Week 16 (Dec. 18) Presentation

1. Problem Sets (30%): Three problem sets (each 10 %). For every assignment, you will analyze one or more of the international datasets introduced in class, applying techniques covered in lectures. Submit both your code (R, Python, Stata, SPSS, or another software) and the resulting output. Collaboration is encouraged, but each student must run the code independently and turn in their own work. Because an answer key is released immediately after the deadline, late submissions are accepted only when an extension is approved in advance or, in an unforeseen emergency, retroactively.


2. Paper Reading Notes (20%): Two assignments (each 10 %). For each, select a journal article that meets the instructor’s criteria and complete structured reading notes by answering guided questions. These tasks build your ability to read research critically and extract insights relevant to your own work.


3. Research Project (40%): Group project for undergraduates; individual project for graduate students. Design and carry out an original empirical study with an international dimension—either a cross-national comparison or an analysis that combines samples from at least two countries. The study must present clear research questions, theory-based hypotheses, appropriate data analysis, and conclusions drawn from the findings. The final paper, written in English, should be about 5,000–10,000 words (excluding references).
   
   
   
   1. 
      
      
      
      1. Proposal (5%): Proposal Workshop on Nov. 6. Written proposal due Nov. 12.
      
      
      2. Presentation (10%): Presentations will take place on Dec. 11 and Dec. 18.
      
      
      3. Final Paper (25%): Due Dec. 24.
      
      
      
      
   
   
   
   


4. Attendance and Participation (10%): You may miss up to three classes without explanation. Additional absences must comply with the National Chengchi University Student Leave of Absence Rules (國立政治大學學生請假規則).

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

• The use of AI tools for basic proofreading is allowed and does not require acknowledgment.


• Any use of AI beyond basic proofreading and text editing must be fully acknowledged, including where and how the AI was used.


• It is prohibited to use AI tools to generate content for assignments without meaningful input from the student.


• Violating this policy will be treated as plagiarism. Consequences may include receiving a zero for the relevant component or the entire assignment. In serious cases, the violation will be reported to the university

Textbook: 

• Sheppard, V. (2024). Research Methods for the Social Sciences: An Introduction. https://open.umn.edu/opentextbooks/textbooks/1589


• Jenkins-Smith, H. C., Ripberger, J. T., Copeland, G., Nowlin, M. C., Hughes, T., Fister, A. L., & Wehde, W. (2017). Quantitative research methods for political science, public policy and public administration (with applications in R). https://shareok.org/server/api/core/bitstreams/f0dc6522-ec87-461b-baa5-2aa604e6e71d/content

All other assigned readings are available from the course website.