The 2024 Conference will include six short courses to enhance your learning experience. These in-depth, half-day courses are taught by well-known experts in the survey research field and cover topics that affect our ever-changing industry. The virtual courses will each have their own registration process, while the in-person course registration will be part of the annual conference registration process.
Cost:
Members: $100/Non-Member: $125
Weighting and Analyzing Nonprobability Samples for Population-Based Inferences
Virtual | May 7, 2024 | 10:00 am – 1:30 pm ET
Instructors: Lingxiao Wang, University of Virginia and Yan Li, University of Maryland
Description:
Making valid population-level inference is a central goal in survey research. While studies with probability sampling are the gold standard to conduct design-based inferences about the target finite population, they are facing substantial challenges such as high costs and reduced response rates in recent decades. As a remedy, nonprobability samples have been increasingly collected in many areas including education, medical studies, and public opinion research. Nevertheless, nonprobability samples cannot well represent the target population due to non-random sampling. Consequently, the naïve nonprobability estimates can be biased from the target population quantities.
Quasi-randomization methods are among the most used approaches to improve representativeness of nonprobability samples. These methods create “pseudoweights” for nonprobability sample individuals using contemporaneous probability surveys as references, which substantially reduce selection bias in estimating target population quantities.
This course will first provide a comprehensive review of the framework for making finite population inferences from nonprobability samples, covering various pseudoweighting methods published in recent literature. Then the attendees will be guided through the specific steps of constructing pseudoweights. To ensure practical application, the course will include software and real-data examples, illustrating how to construct pseudoweights and analyze nonprobability samples, for estimating finite population means and associations.
Using Qualitative Inquiry to Inform Quantitative Data Collection and Analysis
Virtual | May 8, 2024 | 10:00 am – 1:30 pm ET
Instructor: Lila Rabinovich, University of Southern California
Description:
Qualitative methods are increasingly recognized as a valuable addition to quantitative research including survey and experimental studies. There are several channels through which qualitative inquiry can contribute to quantitative research. For instance, qualitative data can help explain the causal mechanisms behind the observed effects of an intervention. It can also provide insights into particular study populations that are difficult to capture well through traditional recruitment methods, thus improving methods of recruitment, retention and measurement. It can help develop and improve quantitative data collection instruments and processes.
This course aims to provide guidance on when and how best to implement these methods. Specifically, the course will explore the ways in which qualitative data collection can support and inform quantitative research design, data collection, and analysis. In particular, the course will focus on actionable recommendations for incorporating qualitative data collection into study designs, including, among others:
• Formative qualitative research to understand a topic more deeply to inform development of hypotheses and survey instruments;
• Formative qualitative research to understand a hard-to-reach population;
• Cognitive testing to check clarity, burden and interpretation of existing survey instruments;
• Developing and pre-testing experimental interventions;
• Understanding/probing survey results.
Participants will be encouraged to bring questions from their own projects for discussion with the group during the workshop.
Questionnaire Design 101
Virtual | May 9, 2024 | 10:00 am – 1:30 pm ET
Instructor: Pam Campanelli, The Survey Coach
Description:
Are you new to questionnaire design or learned on the job, but haven’t had formal training or studied in the past, but would like a refresher? This course is for you. It covers both well-known and less known, but important rules. It covers creating a new questionnaire, trade-offs (clear versus short and simple), the 4 cognitive stages in survey response, question wording guidelines, issues with factual and subjective questions, and problematic question formats to beware of or avoid. An ‘end-of-course’ appendix includes tips for demographic/socio-economic questions and business facts for establishment surveys, the visual side to web surveys, aids to improve respondent recall and reduce question sensitivity, and how these last two concerns differ between surveys for individuals/households and establishments.
Navigating the Privacy-Utility Tradeoff: An Introduction to Data Privacy Techniques
Virtual | May 9, 2024 | 2:00 pm – 5:30 pm ET
Instructors: Claire Bowen, Maddie Pickens, and Gabe Morrison, Urban Institute
Description:
With an increasingly connected and surveilled world, high-quality datasets can be more easily constructed but also are more vulnerable to abuse than ever. Although collecting more and better data can provide great benefits to society, for example by furthering medical research or targeting public investments to help those most in need, data privacy concerns surface when that information can be de-anonymized and used maliciously. This half-day course will provide an overview of current data privacy methodology, focusing on the generation of synthetic data and the application of differentially private methods. Through examinations of case studies and hands-on exercises, you will learn to apply data privacy techniques and evaluate the resulting disclosure risk and data utility. Attendees should have basic R programming experience.
You will be prompted to register for in-person short courses during the conference registration process.
A Practical Introduction to Sensitivity Analyses for Non-ignorable Selection Bias in Surveys
In-Person | May 14, 2024 | 2:00 pm to 5:30 pm ET
Instructors: Rebecca Andridge, Ohio State University and Brady West, University of Michigan
Description:
This short course will provide a hands-on introduction to a set of recently developed indices (SMUB, MUBP) for the assessment of potentially non-ignorable selection bias in estimates computed from nonprobability samples and low response rate surveys. The course will begin with a non-mathematical overview of the indices, including the theoretical underpinnings and model assumptions as well as what data are necessary in order to effectively use these indices. Hands-on computing exercises using publicly available data and R software will walk participants through the use of these indices for a sensitivity analysis. The focus will be on calculation and interpretation of these indices in real-world applications, including data from U.S. pre-election polls, public opinion polls, and large-scale probability surveys with low response rates. The importance of high-quality, population-level auxiliary data for the computation of these indices will be discussed, along with specific recommendations for such data sources. Registered participants will get electronic instructions for installing and starting the R Studio software on their personal laptops prior to the short course. Prior experience with R is not necessary. Participants will also be provided with electronic versions of annotated, working code and data sets prior to the short course, enabling participants to easily follow along without making errors in typing code during the short course.
Cross-cultural Survey Research: Considerations and Best Practices
In-Person | May 14, 2024 | 2:00 pm to 5:30 pm ET
Instructor: Emilia Peytcheva, RTI
Description:
This course will provide an introduction to survey research methods for designing multinational and multicultural surveys. It will focus on measurement error in cross-cultural surveys, but will briefly touch on other sources of error. The course will begin with a theoretical background for cross-cultural differences drawing on cross-cultural psychology and psycholinguistic theories. The discussion of known mechanisms, differences and challenges will be presented within the survey response formation framework.
The second part of this course will focus on translation approaches and best practices. The course concludes with a case study, demonstrating the effect of language on survey responding.
