Training Workshops

Four training workshops will be organized on May 12 by WAPOR as a part of out 78th annual conference program. Participation in training workshops is included into the conference registration package (both professional and student). Every participant can choose one workshop in the morning session and one workshop in the afternoon session.

Morning session on May 12 (09:00-12:00 local time in St Louis, USA)

  • Web Development for Researchers with WordPress (Julia Griffey)
  • Developing Distress Protocols for Survey Research Respondents (Mariel McKone Leonard)

Afternoon session on May 12 (13:00-16:00 local time in St Louis, USA)

  • Data Analysis After Record Linkage (Brady T. West; Priyanjali Bukke)
  • Considering Questionnaire Design through Multiple Theoretical Lenses (Allyson Holbrook)

Web Development for Researchers with WordPress

In the early days of the Web, making even small changes to a webpage required developer assistance, leading to the creation of content management systems (CMS) like WordPress. WordPress, the most popular CMS, powers approximately 43% of websites due to its free, open-source nature and ease of use. It is also highly customizable and has numerous plugins, which can enhance its functionality in almost any way imaginable.

Anyone who wants to publish content to the Web should consider WordPress as their website platform. 

In this workshop, participants will take a deep dive into the world of WordPress. Topics covered will include:

  • Introduction to WordPress: Understand what WordPress is and why it’s the preferred choice for millions of websites worldwide.
  • Setting Up Your Website: Step-by-step instructions on how to install WordPress, choose a domain name, and get hosting.
  • Navigating the Dashboard: Familiarize yourself with the WordPress interface and learn to manage your site effectively.
  • Customizing Your Site: Discover themes and plugins to personalize your website’s appearance and functionality.
  • Creating Content: Learn to create posts and pages, format text, and add images to engage your audience.
  • Basic SEO Tips: Get introduced to essential SEO practices to increase your site’s visibility and attract more visitors.

This workshop is perfect for anyone new to the world of web development. No prior experience or technical knowledge is required—just a willingness to learn and experiment!

Instructor: Prof. Julia Griffey

Julia Griffey is an Associate Professor of Interactive Digital Media and Media Production at Webster University, USA. With over 20 years of experience in web development, Griffey has cultivated a rich and diverse career that bridges technology, design, and education. Holding a BS in Engineering, an MA in Apparel Design, and an MFA in Design, Ms. Griffey integrates technical expertise with creative flair to inspire the next generation of digital innovators. As a published author with two textbooks under Routledge, Griffey contributes significantly to academic literature, sharing insights and methodologies that shape the fields of interactive media and media production. In addition to her academic and professional pursuits, Julia is an avid designer, coder and content creator, and runs several highly trafficked websites. Her unique blend of skills and experiences makes Griffey a distinguished leader and influencer in the realm of interactive media and media production.

Data Analysis After Record Linkage

As a common and detailed approach to data integration, record linkage is essential to match data on the same entity spread across multiple files. At the same time, record linkage is not necessarily error-free. Data belonging to different entities may be linked incorrectly, or links between data on the same entity may be missed. In consequence, the quality of the resulting data can be significantly reduced. It is, therefore, advisable to suitably adjust downstream statistical analysis to account for potential bias caused by data contamination because of incorrect links or sample selection introduced by missing links. However, information pertinent to adjustment may be limited or absent due to reasons such as privacy considerations. This challenge especially occurs in the secondary analysis setting, which is becoming increasingly important as data users may not be able or willing to perform record linkage. This beginner-level course will equip attendees to (1) recognize possible sources and consequences of linkage errors, (2) identify methods to account for linkage errors in the secondary analysis setting, (3) use R software to conduct such data analysis in practice, and (4) discuss open problems based on the existing methodologies and their software implementation. Attendees will have the option to run R code presented, in real-time. Set-up instructions will be made available beforehand, and we will walk through code and output from example case studies step-by-step during the session.

Instructors: Brady T. West; Priyanjali Bukke.

Brady T. West is a Research Professor in the Survey Methodology Program, located within the Survey Research Center at the Institute for Social Research on the University of Michigan-Ann Arbor (U-M) campus. He earned his PhD from the Michigan Program in Survey and Data Science in 2011. Before that, he received an MA in Applied Statistics from the U-M Statistics Department in 2002, being recognized as an Outstanding First-year Applied Masters student, and a BS in Statistics with Highest Honors and Highest Distinction from the U-M Statistics Department in 2001. His current research interests include the implications of measurement error in auxiliary variables and survey paradata for survey estimation, selection bias in surveys, responsive/adaptive survey design, interviewer effects, and multilevel regression models for clustered and longitudinal data. He is the lead author of a book comparing different statistical software packages in terms of their mixed-effects modeling procedures (Linear Mixed Models: A Practical Guide using Statistical Software, Third Edition, Chapman Hall/CRC Press, 2022), and he is also the lead author of a second book entitled Applied Survey Data Analysis (with Steven Heeringa and Pat Berglund), the third edition of which will be available in early 2025. He was elected as a Fellow of the American Statistical Association in 2022.

Priyanjali Bukke is a Ph.D. student in Statistics at the University of Virginia. Her research interests include data integration and its relation to data privacy and quality. Supported by the NSF, Priyanjali is involved in a collaborative project under the supervision of Martin Slawski and Brady West to develop a new framework for analyzing data resulting from imperfectly merging files. She is also maintaining open-source software in R to implement this framework.

Developing Distress Protocols for Survey Research Respondents 

When conducting sensitive survey research or working with vulnerable populations, it may be necessary to have a safety protocol in place should research participants experience distress by the topics discussed.

This short course will provide participants an introduction to developing distress protocols for survey respondents, including:

  • When and why survey research might need a distress protocol.
  • Basic elements of a distress protocol.
  • Overview of best practices for developing distress protocols.
  • National helplines and resources to include as supporting materials.
  • Distress protocols and supporting materials to include in ethics/IRB review package.

Throughout the course, participants will have opportunities to share their own experiences and lessons learned, as well as work in small groups to outline elements required for their own distress protocols.

By the end of the course, participants will be able to: (1) Determine if their project should include a distress protocol; (2) Outline components of a distress protocol appropriate for their project; and (3) Prepare distress protocol materials for inclusion in an ethics/IRB review package.

Anyone who is considering conducting a survey on sensitive topics or with vulnerable populations should attend this course. Prior experience with sensitive topics, vulnerable populations, or distress protocols is not necessary but is welcome.

Instructor: Dr. Mariel McKone Leonard

Mariel McKone Leonard is a survey methodologist with over a decade of experience in the field. Her main areas of research are improving representation of minority groups in research studies, including are methods of probability and non-probability sampling special populations, as well as conducting research within sensitive contexts. In both contexts, her work focuses on innovating and improving methods in an ethical and participant-focused manner. She received her doctorate at the University of Mannheim in 2020, before which she worked at Westat as a research assistant in the Telephone Research Center and the Instrument Design, Evaluation, and Analysis Services group. Additionally, she is a trained crisis counselor.

Considering Questionnaire Design through Multiple Theoretical Lenses

There is a large body of literature on questionnaire design that is constantly evolving to address new methods, modes, and populations. It can be difficult to synthesize this literature into a coherent set of guidelines. This short course will consider questionnaire design through relevant theoretical lenses, with a special emphasis on considering cross-national or cross-cultural surveys. Participants who enroll in the work shop will learn:

  • The primary goals of questionnaire design.
  • How researchers evaluate questionnaire design.
  • How other elements of survey design (e.g., mode, population, topic) affect questionnaire design
  • How to think about questionnaire design through four major theoretical lenses:
    • Surveys as a cognitive task.
    • Surveys as a conversation.
    • Surveys as a social interaction.
    • (Some) surveys as a visual processing task.

Throughout the course, participants will have the opportunity to share their own experiences and expertise, as well as being able to ask questions specific to their questionnaire design needs. By the end of the course, participants will be able to: (1) understand the goals of questionnaire design, (2) know how to collect and use survey data to evaluate different questionnaire designs, (3) understand the implications of other aspects of survey design for questionnaire design, and (4) be able to think about a questionnaire through the four relevant theoretical lenses. 

Instructor: Prof. Allyson Holbrook

Allyson Holbrook is a Professor of public policy, management, and analytics and psychology (by courtesy) in the College of Urban Planning and Public Affairs at the University of Illinois Chicago (UIC). She is a social psychologist and survey methodologist whose research and teaching addresses survey design, particularly questionnaire design. She has taught at UIC since 2002 and also spent over a decade working on applied survey data collection projects with the UIC Survey Research Laboratory. She is a current co-Editor-in-Chief of the journal Public Opinion Quarterly.