Survey Design

Claudia von Vacano, Ph.D.

Founding Executive Director, P.I., Research Director, FSRDC

Dr. Claudia von Vacano is the Founding Executive Director and Senior Research Associate of D-Lab and Digital Humanities at Berkeley and is on the boards of the Social Science Matrix and Berkeley Center for New Media. She has worked in policy and educational administration since 2000, and at the UC Office of the President and UC Berkeley since 2008. She received a Master’s degree from Stanford University in Learning, Design, and Technology. Her doctorate is in Policy, Organizations, Measurement, and Evaluation from UC Berkeley. Her expertise is in organizational theory and...

Field Experiments in Corporations

January 28, 2025
Yue Lin
by Yue Lin. How do social science researchers conduct field experiments with private actors? Yue Lin provides a brief overview of the recent developments in political economy and management strategy, with a focus on filing field experiments within private corporations. Unlike conventional targets like individuals and government agencies, private companies are an emergent sweet spot for scholars to test for important theories, such as sustainability, censorship, and market behavior. After comparing the strengths and weaknesses of this powerful yet nascent method, Lin brainstorms some practical solutions to improve the success rate of field experimental studies. She aims to introduce a new methodological tool in a nascent research field and shed some light on improving experimental quality while adhering to ethical standards.

Causal Inference in International Political Economy: Hurdles and Advancements

September 9, 2024
Yue Lin
by Yue Lin. What are the key challenges and opportunities of applying experiments in the International Political Economy (IPE) research? In this blog, I reviewed an enduring methodological battle between statistics and experiments, and pointed out that the difficulties of randomization and locating credible counterfactuals have served as main hurdles for IPE scholars to widely adopt experimental tools. However, I further demonstrated some new progress in applying survey, field, and lab experiments in the recent IPE scholarship. I concluded that it is crucial for future researchers to think innovatively about how to combine different research methods to make causal claims in IPE studies.

Survey Fundamentals

February 21, 2024, 1:00pm
This two-hour workshop offers a comprehensive introduction to designing and conducting survey studies. Tailored for beginners, it provides clear, step-by-step guidance complemented by concise examples, practical considerations, and useful support materials. Participants will learn the entire process, from formulating a research question to creating, administering, and analyzing surveys, as well as interpreting results and communicating their findings.

Survey Fundamentals

April 11, 2024, 3:00pm
This two-hour workshop offers a comprehensive introduction to designing and conducting survey studies. Tailored for beginners, it provides clear, step-by-step guidance complemented by concise examples, practical considerations, and useful support materials. Participants will learn the entire process, from formulating a research question to creating, administering, and analyzing surveys, as well as interpreting results and communicating their findings.

Transparency in Experimental Political Science Research

April 9, 2024
Kamya Yadav
by Kamya Yadav. With the increase in studies with experiments in political science research, there are concerns about research transparency, particularly around reporting results from studies that contradict or do not find evidence for proposed theories (commonly called “null results”). To encourage publication of results with null results, political scientists have turned to pre-registering their experiments, be it online survey experiments or large-scale experiments conducted in the field. What does pre-registration look like and how can it help during data analysis and publication?

Design Your Observational Study with the Joint Variable Importance Plot

March 12, 2024
Lauren Liao
by Lauren Liao. When evaluating causal inference in observational studies, there often is a natural imbalance in the data. Luckily, variables are often measured alongside that can be helpful for adjustment. However, deciding which variables should be prioritized for adjustment is not trivial – since not all variables are equally important to the intervention or the outcome. I recommend using the joint variable importance plot during the observational study design phase to visualize which variables should be prioritized. This post provides a gentle guide on how to do so and why it is important.

From Ideas to Streamlined Research: The Benefits of Full-Cycle Methodology

December 5, 2023
Farnam Mohebi
by Farnam Mohebi. As an aspiring leading researcher, I find the full-cycle research methodology crucial for transforming initial curiosities into organized studies and research products. This approach begins with thorough observation, leads to theory and hypothesis development and experimentation, and concludes with synthesizing findings into coherent narratives. It's beneficial for researchers of all backgrounds, enhancing the depth and impact of their work. By embracing this method, researchers comprehensively understand each stage and its contribution to the broader research context and can lead the process of converting an initial unspecified research idea to a streamlined research study and product. This systematic approach is particularly effective in complex studies, fostering thorough, investigative, and innovative research processes.

Introduction to Item Response Theory

October 24, 2023
Mingfeng Xue
by Mingfeng Xue. Measurements (e.g., tests, surveys, questionnaires) are inevitably involved with various sources of errors. Among many psychometric theories, item response theory stands out for its capability of detailed analyses at the item level and its potential to reduce some of the measurement errors. This post first discussed the limitations of conventional summation and average, which give rise to the IRT models, and then introduced a basic form of the Rasch model, including expressions of the model, the assumptions underlying it, some of its advantages, and software packages. Some codes are also provided.

FSRDC 2023 Annual Meeting and Research Conference

October 2, 2023
Renee Starowicz, Ph.D.
by Renee Starowicz. Renee Starowicz, Co-Executive Director of the Berkeley Federal Statistical Research Data Center, provides an overview of the takeaways from the 2023 Annual Federal Statistical Research Data Center Business Meeting and Annual Conference. She provides a brief overview of the Berkeley FSRDC. Then, she describes the priorities for collaboration across national directors to improve outreach to diverse researchers and transparency. Additionally, she points out the other key topics of conversation at this year’s meeting.