Workshops
Table of Content
- How Do You Teach a Short Workshop on Methods? Tips, Tricks, and Other Advice from Experience
- Data and Model Visualization
- Capturing and Measuring ‘Experiences’ in Everyday Life: An Overview of Ecological Momentary Assessment
- Qualitative Research in Health Sciences: Benefits, Approaches, Limitations, and Ethical Considerations
- Observational Coding Methods Applied to Child Play Behavior
- Data Collection in the Transnational Context
- Data Management and Other Fundamentals for Efficient and Reproducible Research
- Approaches to Handling Missing Data
- Stata Programming: Tools & Tricks for the Applied Analyst
- Conducting Survey Experiments to Test Causality
- Survey Design Workshop
- Current Research on Biases in the Measurement of Thoughts, Feelings, and Behaviors
How Do You Teach a Short Workshop on Methods? Tips, Tricks, and Other Advice from Experience
Dr. Trent Mize, Associate Professor of Sociology (February 2023)
Data and Model Visualization
Dr. Trent Mize, Associate Professor of Sociology (March 2018)
- updated slides in Fall 2022
Capturing and Measuring ‘Experiences’ in Everyday Life: An Overview of Ecological Momentary Assessment
Dr. Louis Tay, William C. Byham Associate Professor in Industrial-Organizational Psychology,
Department of Psychological Sciences, Purdue University (February 2020)
Qualitative Research in Health Sciences: Benefits, Approaches, Limitations, and Ethical Considerations
Elizabeth Kielb, Ph.D. candidate in the Department of Human Development and Family Science and AMAP Certificate Student; Carly Kimiecik, doctoral student in the Department of Public Health (February 2023)
The purpose of this workshop is to provide an introduction to qualitative research within the health sciences. This will include an overview of common qualitative approaches, recruitment strategies, ethical considerations, analytic approaches, considerations for data storage and software packages, and suggestions for further training in qualitative methods. This workshop will also include interactive activities and opportunities for group discussions around introducing qualitative methods into different fields of research.
Observational Coding Methods Applied to Child Play Behavior
Dr. Lindsey M. Bryant, Human Development and Family Studies and AMAP Certificate Student (August 2022)
This seminar provides a brief introduction to developing or expanding observational coding systems within the context of preschoolers' play behavior. Methodological considerations of observational coding (e.g., reliability, validity, nested data) as well as complications and extensions of these approaches will be discussed. Two primary examples will be used to explore these topics. First, adapting an existing measure for recess quality to preschool-aged settings (live coding). Second, developing and applying a coding scheme to evaluate mathematical language usage during a preschool block play intervention (video/transcription data).
Data Collection in the Transnational Context
YounEun Nam, PhD student in the Department of Sociology and AMAP Certificate Student; Vasundhara Kaul, PhD student in the Department of Sociology and AMAP Certificate Student (September 2020)
Workshop Structure:
- Transnational vs. International Research
- Group Activity & Discussions
- Step 1: Choosing the Site
- Step 2: Recruitment
- Step 3: Translation and Language
- Step 4: IRB Process
- Step 5: Budgeting
- Step 6: Navigating Cultural Norms • Group Activity
- Discussion & Final Questions.
Data Management and Other Fundamentals for Efficient and Reproducible Research
Dr. Trent Mize, Associate Professor of Sociology (Fall 2019)
Abstract: Issues of reproducibility and replication increasingly dominate conversations across the behavioral, data, health, and social sciences. Good workflow practices ensure that all stages of the research process—from reviewing and saving relevant literature, sharing files among collaborators, using software effectively, and conducting data management and analysis tasks—can be done effectively, efficiently, and accurately. The research process contains many steps and—often—thousands of files. Mistakes at any stage of the process—be it the planning, documenting, data collection, data cleaning, variable creation and manipulation, data analysis, writing, replicating, and preserving stages—can waste time and cause unnecessary stress. This workshop will provide practical and easily implementable best practices for anyone who deals with quantitative data in their research—ensuring their workflow leads to accurate and reproducible research results. The methods discussed in the workshop are general and not tied to any particular software package for data analysis.
Approaches to Handling Missing Data
Dr. Trent Mize, Associate Professor of Sociology (November 2019)
Abstract: Very little data of interest to social, behavioral, and health scientists contains complete information. Instead, some missing data tends to be the rule rather than the exception in applied data analysis. Survey respondents may choose to skip sensitive questions; economic data may be harder to find for developing countries; certain types of respondents may be most likely to drop out of panel studies. Rarely is data “missing completely at random” — instead there tend to be systematic factors accounting for missing observations — factors that can bias results if not properly handled.
This workshop will focus on the most effective techniques for conducting quantitative analyses with missing data. In addition to covering the basics of missing data theory and showing the problems that can occur when ignoring missing data, we will cover in detail methods for: (1) multiply imputing missing data, (2) handling missing data with hotdeck imputation, and (3) full information maximum likelihood. Which method to use depends on many factors idiosyncratic to different analyses. The workshop focuses primarily on the methods rather than statistical software; however example code and resources will be provided for implementing the methods in Stata and R, along with some resources for handling missing data in SAS and SPSS.
Stata Programming: Tools & Tricks for the Applied Analyst
Dr. Trent Mize, Associate Professor of Sociology (Fall 2019)
Abstract: Stata is an increasingly popular tool for data analysis across the social, behavioral, and health sciences. Stata strikes an elegant balance between ease of use on the one hand, and in customizability and sophistication on the other. This workshop focuses on the bread and butter programming tools and tricks for applied data analysts—ensuring data management and data analysis tasks are done efficiently and accurately. Knowing even a little bit of advanced coding can greatly increase the speed and accuracy of many common tasks. The workshop focuses both on ways to customize Stata to make it a more effective research tool and on selected topics in data management, data analysis, and programming. Only a working knowledge of Stata is necessary to participate in the workshop—no expert knowledge is assumed.
Conducting Survey Experiments to Test Causality
Dr. Trent Mize, Associate Professor of Sociology (January 2019)
Abstract: Experimental designs remain the gold standard for assessing causality; perhaps because of this, the use of experiments has grown rapidly in most social science fields such as economics, political science, sociology, and others. While laboratory studies remain popular in some fields, there is increasing interest in bringing the power of experimental designs to more diverse samples. Survey experiments offer the capability to assess causality in a broad range of samples, including targeted samples of specific populations or in large-scale nationally representative samples. The rise of online workplaces and the TESS program offer the ability to bring these samples to applied researchers at a minimal cost, greatly expanding the possibilities for research. This workshop will focus on how to design quality survey experiments, giving researchers the tools to implement best practices. I will also advocate for survey experiments as a tool for tests of intersectionality and other theoretical questions requiring diverse samples.
Survey Design Workshop
Dr. Trent Mize, Associate Professor of Sociology (November 2018)
Abstract: Designing quality surveys is difficult. There are a myriad of choices for how to word a survey question, what answer choices to use, how to format response options, whether to ask one question or multiple related questions, how to frame the instructions, and much more. Fortunately, a large and growing literature on best practices for survey design offers useful guidance for these and other choices. The focus of the workshop will be on applying research insights into best practices for designing surveys; while the focus will be on the methods, there will also be examples throughout of how to implement these practices using Qualtrics.
Current Research on Biases in the Measurement of Thoughts, Feelings, and Behaviors
Dr. Sane Lane, Assistant Professor of Psychological Science (March 2018)
Workshop Structure:
- The phenomenon of interest
- First set of studies
- Experimentally establishing the effect
- Exploring two possible mechanisms
- New analyses
- Additional measures
- Possible physiological mechanism
- Methodological Implications
- Correlational vs. experimental studies
- Simulations
- Conclusions