EDF 6471— Survey Design and Analysis in Educational Research
Summer 2025
Professor: Dr. Walter Leite
E-mail: walter.leite@coe.ufl.edu
Course Description
This course prepares students to plan and implement surveys and analyze data from complex national and international surveys.
This course is under review for UF’s Enable-AI course designation. An AI-enabled course supports AI through related knowledge and skill development, such as programming or statistics. The AI course content for this designation is 10-49%.
Student Learning Objectives:
1. Create a plan for survey development, pre-testing, and implementation
2. Write and format surveys for online, mail, group, and mixed-model administration.
3. Implement a survey to maximize response rates
4. Calculate sampling, non-response, and post-stratification weights
5. Identify and use survey weights from national and international surveys
6. Handle missing data in surveys appropriately
7. Estimate and interpret regression models with complex weights
8. Obtain correct standard errors for regression coefficients, adjusting for clustering and strata effects
9. Fit and interpret fixed effects and random effects regression models
10. Evaluate the sensitivity of regression results to missing data assumptions and omitted confounders
Pre-requisite:
The pre-requisite for this class is EDF6403, or EDF6402, or EDF7405
Required books:
Dillman, D., Smyth, J., Christian, L. M. (2008). Internet, Mail, and Mixed-Mode Surveys: The Tailored Design Method, 3rd Edition. New York, NY: John Wiley & Sons, Inc. Steven G. Heeringa, Brady T. West, Patricia A. Berglund (2018). Applied Survey Data Analysis. Routledge.
Additional readings will be provided on Canvas.
Recommended books:
Krueger, R. A. & Casey, M. A. (2009). Focus groups: a practical guide for appliedresearch. 4th edition. Newbury Park, CA: Sage Publications.
Lumley, T. (2010). Complex surveys: A guide to analysis using R. New York, Wiley.
Software:
I will use R and RStudio software for statistical analyses.
Recommended website for survey data analysis with R.
Calendar of Topics
Week 1 –- Introduction, project planning, overview of resources
Week 2 – Population definition; sampling methods
Week 3 –– Preliminary survey planning, choice of survey method, Calculation of sample size
Week 4 – Focus groups for question development, Question writing
Week 5 – Question writing
Week 6 – Questionnaire Construction
Week 7 – Pre-testing
Week 8 – Implementation of mail surveys, implementation of internet surveys
Week 9 – Implementation of group-administered surveys and mixed-mode surveys
Week 10 – Sampling weights, post-stratification, raking, and calibration
Week 11 – Missing Data
Week 12 – Regression with sampling weights
Week 13 – Cluster-robust standard errors, Bootstrapping and jackknife
Week 14 – Fixed effects and random effects models
Week15 –– Sensitivity analysis