- Instructor: Sebastian Daza
- Email: sebastian.daza@gmail.com
- Location: 2.A.04:1
- Wednesdays 18:00 - 20:45
- Office hours: by appointment
This course is an introduction to survey methodology. We will review how survey data are generated, their limitations, and how to perform adjustments and analysis to get the correct estimates. The course examines the mode of interview, sampling concepts, and issues in instrumentation. Most of the course is spent reviewing research that describes the effect of survey design features on survey error and applied techniques to create a sample and analyze survey data.
This course consists of lectures and activities in and out of the classroom. Upon successful completion of the course, you should be able to understand the potential and limits of survey methodology and connect them with data science challenges and issues.
Readings of the course combine book chapters and research papers. All the readings will be available through Zotero. It would be best if you asked to be part of the course group here to access research papers and books. Please, create an account if you don't have one.
The key books of the course are:
- SM = Groves, Robert M., Floyd J. Fowler Jr, Mick P. Couper, James M. Lepkowski, Eleanor Singer, and Roger Tourangeau. 2009. Survey Methodology. 2nd ed. Wiley.
- HSM = Gideon, Lior, ed. 2012. Handbook of Survey Methodology for the Social Sciences. New York, NY: Springer New York.
- HSR = Marsden, Peter V., and James D. Wright, eds. 2010. ** Handbook of Survey Research**. Second edition. Bingley, UK: Emerald.
- TSE = Biemer, Paul P., Edith Desirée de Leeuw, Stephanie Eckman, Brad Edwards, Frauke Kreuter, Lars Lyberg, Clyde Tucker, and Brady T. West, eds. 2017. Total Survey Error in Practice. Hoboken, New Jersey: Wiley.
The course combines lectures, short student presentations, and practical exercises. We will read approximately two chapters/articles per week.
Students' grades will depend on the following:
- Active participation (discussion) + short presentations during the class (25%)
- Weekly short assignments (25%)
- Final project (50%)
In each class, each student will present one research paper in about 5 minutes (no slides) as a way to practice the elevator speech. Each presentation should be able to summarize a paper by presenting the question o problem it's trying to solve, why it's important, how authors face the issue, the results conclusion, good features, and limitations of the paper or chapter. The rest of the students will ask questions to the presenter after the presentation.
There will be 2-3 practice exercises. They will sometimes be the base for class discussion.
This project requires you to write a brief proposal to conduct a survey. I will provide a detailed description of the proyect at least three weeks before the project is due. You must work independently on this project. The maximum length is ten pages of text. All course papers must be written professionally following the format: at least 1-inch margins, double-spaced, 12 font size (Times New Roman), and page-numbered.
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Syllabus introduction
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Introduction to survey methodology
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Total error concept
- SM Chapter 2: Inference and errors in surveys
- Chapter 1: New Directions in Public Opinion (The Practice of Survey Research Changes and Challenges)
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Conceptualization and measurement
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Measurement error, reliability, validity
- Chapter 4: Making sense of the social world, methods of investigation (Conceptualization and Measurement)
- TSE Chapter 2: Total Twitter Error
- TSE Chapter 3: Big Data A Survey Research Perspective
- Panel Conditioning in Longitudinal Social Science Surveys
- HSR Chapter 12: How good is survey measurement? Assessing the reliability and validity of survey measures
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Methods of data collection
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Questionnaire design and evaluation
- SM Chapter 5: Methods of data collection
- Chapter 7: Making sense of the social world: methods of investigation (Survey Methodology)
- HSR Chapter 17: Mixed-mode surveys
- HSR Chapter 16: Internet Surveys
- HSM Chapter 20: Building your own online panel via e-mail and other digital media
- HSM Chapter 24: What Survey Modes are Most Effective in Eliciting Self-Reports of Criminal or Delinquent Behavior?
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Introduction to statistical concepts
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Introduction to sampling
- SM Chapter 3: Target populations, sampling frames, and coverage error
- HSM Chapter 7: The art of question phrasing
- Social Desirability Bias in CATI, IVR, and Web Surveys: The Effects of Mode and Question Sensitivity
- HSR Chapter 13: Interviewers and interviewing
- HSM Chapter 22: Sensitive issues in surveys
- The Science of Asking Questions
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How to design a sample
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Sampling strategies
- SM Chapter 4: Sampling design and sampling error
- Sampling and Estimation in Hidden Populations Using Respondent-Driven Sampling
- The Impact of Survey Mode Design and Questionnaire Length on Measurement Quality
- Beyond Power Calculations Assessing Type S (Sign) and Type M (Magnitude) Errors
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Selection of samples using R
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Analyzing complex survey data
- SM Chapter 10: Postcollection processing of survey data
- Struggles with Survey Weighting and Regression Modeling
- Predicting State Presidential Election Results Using National Tracking Polls and Multilevel Regression with Poststratification (MRP)
- Failure and Success in Political Polling and Election Forecasting
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Analyzing complex survey data (continuation)
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Sample adjustments
- Measuring public opinion with Surveys
- The State of Survey Methodology: Challenges, Dilemmas, and New Frontiers in the Era of the Tailored Design