RESOURCES

Workshops

MCAP hosts a variety of one and two-day workshops on a wide range of advanced methodological methods. And we make workshop slides, videos, and/or related materials free to the public to promote methodological learning.

Table of Contents

Longitudinal Network Analysis Workshop
Special Topic: Temporal Exponential Random Graph Models for Longitudinal Network Analysis

Dr. Scott Duxbury, Associate Professor, UNC (September 2025)

Slides and Code Here

Researchers increasingly examine relational data structures. This workshop will introduce the class of exponential random graph models (ERGM) for social network analysis, with a focus on temporal ERGM (TERGM) for repeated network measures.
Topics covered will include:
(1) modeling capabilities and data requirements
(2) specification of temporal and structural dependencies
(3) estimation, model fitting, and model checking
(4) modeling assumptions (and when to know they’re violated!)
(4) interpretation.
Additional topics to be covered if time permits include mediation analysis using TERGM, simulation, and hypothesis testing on micro-macro linkages.

• Introduction to R
• Dr. Katie Thompson, Postdoctoral Associate, Sociology (September 2025)
• Slides and R Files
• In this session, I will provide a (hopefully engaging) introduction on how to use R within R Studio. This will begin with absolute basics of going through what R looks like, key elements of the R language, useful packages, tools to efficiently manage data, reviewing unique data structures for repeated measures/longitudinal data, and describe template code for commonly use statistical models. No prior R knowledge expected, but download R and R Studio to follow along with the content.

• Building Strong Research Foundations: How to Design and Publish Your Simulation-Based Power Analysis
• Dr. Yongseok Lee, Postdoctoral Associate, Department of Human Development and Family Science (April 2025)
• Slides
• R files
• Simulation-based power analysis is a flexible, robust approach for designing complex studies that require more than power analysis under simplified assumptions. In this applied workshop, researchers from diverse fields willbe introduced to the core concepts of simulation-based power analysis, including how to generate data reflecting  real-world complexities, conduct analysis on simulated datasets, repeat this process systematically, visualize and interpret key performance metrics including power. We will use R and G*power to demonstrate practical examples. By the end of the session, participants will be equipped to design simulation-based power analysis tailored to their own research needs, thereby enhancing their ability to produce meaningful results and avoid common pitfalls in hypothesis testing.
• This workshop is designed for researchers and graduate students with some familiarity in statistics or quantitative methods; however, no prior experience with simulation or power analysis is required.

• A Social Scientist’s Introduction to Item Response Theory
• Dr. Brooke Magnus, Associate Professor of Psychology and Neuroscience at Boston College (March 2025) 
• Slides
• Example R code
• Example Stata code
• Item Response Theory (IRT) is a powerful framework for analyzing item-level data in psychology, education, and social sciences. This applied workshop will introduce participants to the fundamentals of IRT, emphasizing its connection to item factor analysis and exploring models for binary, ordinal, and nominal data. Key topics will include model assumptions, item/model fit evaluation, and scoring, with a heavy focus on data visualization and interpretation. The workshop will primarily use R, but some Stata demonstrations will also be provided. By the end of the session, attendees will have a solid foundation in unidimensional IRT and be equipped with the tools to apply IRT models to their own research. Time permitting, we will also discuss advanced topics, including differential item functioning and IRT models with more than one latent variable.
• This workshop is designed for researchers and graduate students with some familiarity with statistical modeling, but no prior experience with IRT is required.

• Intro to Deep Learning Models and Application to Social Sciences
• Dr. Rafael Geurgas (Post-Doc, Sociology, Purdue University)
• Slides

• 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) 
• slides and recording below.

• Data and Model Visualization
• Dr. Trent Mize, Associate Professor of Sociology (March 2018)
• updated slides in Fall 2022. See recording below.

• 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)
• slides

• Qualitative Research in Health Sciences: Benefits, Approaches, Limitations, and Ethical Considerations
• Dr. Lindsey M. Bryant, Human Development and Family Studies and AMAP Certificate Student (August 2022) 
• slides
• 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). 

• Observational Coding Methods Applied to Child Play Behavior
• 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)
• slides
• 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. 

• Data Management and Other Fundamentals for Efficient and Reproducible Research
• Dr. Trent Mize, Associate Professor of Sociology (Fall 2019)
• slides
• 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.

• Data Collection in a Transnational Context
• YoungEun 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)
• slides
• 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. 

• Stata Programming: Tools & Tricks for the Applied Analyst
• Dr. Trent Mize, Associate Professor of Sociology (Fall 2019)
• slides
• 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)
• slides
• 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)
• slides
• 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. Sean Lane, Assistant Professor of Psychological Science (March 2018) 
• slides
• 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 

Resources for grants

MCAP provides several services to support students and faculty with regard to grants.

Do you need a statistical or methodological consultant to support a grant proposal, but aren’t sure where to look?

Email mcap@purdue.edu. We can help you identify and connect with an affiliated faculty member to help establish a collaboration.

Do you want to include MCAP in your facilities and other resources section?

Here is some text that you can include and/or modify to suit your needs. Feel free to reach out to mcap@purdue.edu with any questions or if you need help tailoring the text to your grant.

The Methodology Center at Purdue (MCAP) is cross-college center working towards increasing methodological expertise and collaborative opportunities in the behavioral, health, and social sciences. The Methodology Center has fostered a strong support system for advanced statistics and methodology, including workshopping, aiding in study design, troubleshooting data issues, and conducting statistical analyses. MCAP facilitates interdisciplinary collaboration by hosting a monthly work-in-progress seminar series, regular workshops, and facilitating external speakers for talks and conferences. MCAP creates an atmosphere of diverse analytical perspectives. Affiliates have deep expertise in qualitative methodologies, experimental design, econometric modeling, data visualization, and computational ‘big data’ analysis, among other areas. MCAP also offers open consultation, and an interdisciplinary research methods certificate program to enhance methodological training of the next generation of scientists. Thus, MCAP provides a strong resource (i.e., though methodological and statistical consultation) to help facilitate the success and rigorous work of the health and social sciences. 

Do you want to leverage MCAP to bolster your training?

Check out our certificate program. We can also help to identify mentors for training grants, and if it makes sense for the proposal, to provide a letter of support. Email mcap@purdue.edu with questions.