WOrkshops
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.
- Dr. Vasundhara Kaul, Post-Doctoral Research Associate, Sociology and MCAP Purdue University; Post-Doctoral Affiliate, GRAIL (March 2026)
- Slides and Code here
- Abstract: How do algorithms “read” emotion in text—and what happens when language is reduced to a numeric sentiment score? Sentiment analysis is widely used in social research, public policy, marketing, and digital media to measure public opinion and affect at scale. This hands-on workshop introduces participants to the basic ideas behind sentiment analysis and its practical implementation using Python. We will explore three common approaches—dictionary-based methods, supervised machine learning, and transformer-based models—and examine how each interprets emotion differently. Through guided coding exercises, participants will generate and compare sentiment predictions, while reflecting on common challenges such as sarcasm, context, and bias. The workshop emphasizes both practical skills and critical reflection, helping participants better understand how sentiment analysis can be best used in their own research. This workshop is beginner-friendly, and no prior experience with Python or coding is required.
- Dr. Scott Duxbury, Associate Professor, UNC (September 2025)
- Slides here
- Abstract: 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!), (5) interpretation. Additional topics to be covered if time permits include mediation analysis using TERGM, simulation, and hypothesis testing on micro-macro linkages.
- Dr. Katie Thompson, Postdoctoral Associate, Sociology (September 2025)
- Slides and R Files
- Abstract: 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.
- Dr. Yongseok Lee, Postdoctoral Associate, Department of Human Development and Family Science (April 2025)
- Slides and Code here
- Abstract: 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.
- Dr. Brooke Magnus, Associate Professor of Psychology and Neuroscience at Boston College (March 2025)
- Slides and Code here
- Abstract: 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.
- Dr. Rafael Geurgas, Post-Doc, Sociology, Purdue University (February 2025)
- Slides here
- Dr. Trent Mize, Associate Professor of Sociology (February 2023)
- Slides here
- Video recording of the workshop
- 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 here
- Abstract: 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.
- Dr. Lindsey M. Bryant, Human Development and Family Studies and AMAP Certificate Student (August 2022)
- Slides here
- Abstract: 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).
- Beth Ann Labadorf, Phd. CandidateBrian Lamb School of Communication, Purdue University (Fall 2023)
- Slides here
- Dr. Elyssa Geer, Assistant Professor at the University of Florida (Sprinf 2022)
- Slides and Code here
- 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 here
- Dr. Louis Tay, William C. Byham Associate Professor in Industrial-Organizational Psychology,Department of Psychological Sciences, Purdue University (February 2020)
- Slides here
- Video Resource
- Dr. Trent Mize, Associate Professor of Sociology (Fall 2019)
- Slides here
- 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.
- Dr. Trent Mize, Associate Professor of Sociology (Fall 2019)
- Slides here
- 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.
- Dr. Trent Mize, Associate Professor of Sociology (January 2019)
- Slides here
- 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.
- Dr. Trent Mize, Associate Professor of Sociology (November 2018)
- Slides here
- 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. Trent Mize, Associate Professor of Sociology (March 2018)
- Slides here
- Video recording of the workshop here
- Dr. Sean Lane, Assistant Professor of Psychological Science (March 2018)
- Slides here
Course OFferings
Methods Courses at Purdue
The following list is intended as a resource for graduate students at Purdue interested in taking methods courses. We update the list every semester. The semester listed for each course means the most recent year when the course is, or will be, offered.
Many of these courses qualify for the MCAP Graduate Certificate (see the full list of qualifying courses here).
- HDFS 607/ COM 682 – Interdisciplinary Graduate Methods (Jeremy Foote, David Purpura)
- ANTH 592 – Ethnographic Writing (Andrew Flachs)
- ANTH 605 – Seminar in Ethnographic Analysis (Courtney Thomas Wittekind)
- ANTH 640 – Applying Anthropology (Sarah Renkert)
- COM 582 – Descriptive/Experimental Research In Communication (Jessica Collier)
- COM 597 – Mediation and Moderation Models (Ilwoo Ju)
- CPB 626: Design and Analysis of Epidemiologic Studies
- HDFS 613 – Quantitative Methods I (Sharon Christ)
- HDFS 627 – Multilevel Model Development & Family Research (Kristine Marceau)
- HTM 601 – Research Development & Design (Alei Fan, Rodney Carl Runyan)
- HTM 690: Research Problems in HTM (Multiple Instructors)
- ILS 540 – Critical GIS (Melissa Chomintra)
- ILS 595 – GIS Research Methods (Innocensia Achieng Owuor)
- ILS 630 – Digital Humanities Foundations (Spencer Stewart)
- LING 598:Introduction to Corpus Linguistics with Python (Atushi Fukada)
- LING 598: Statistical Modeling for Linguistics (Yan Cong)
- NUR 626: Applied Biostatistics for Outcome Evaluation
- NUR 692: Applied Statistics in Healthcare Research
- POL 501: Political Science: Methodology (Joan Timoneda)
- POL 606: Experimental Methods in Social Sciences (Tara Grillos)
- POL 693: Introduction to Modeling Social-Tech and Socio-Eco Systems (David Yu)
- PSY 606: ANOVA Behavioral Sciences (Stephen B. Broomell)
- PSY 681: Research Methods IO Psychology (Franki Kung)
- PUBH 526: Randomized Control Trials (Nilupa Gunaratna)
- PUBH 601: Introduction to Quantitative Methods in Public Heath (Shandey Malcolm)
- PUBH 606: Design/Analysis in Public Health (Melissa Kenzig)
- SOC 581: Methods of Social Research (Evelina Akimova)
- SOC 681: Categorical Data Analysis (Trenton Mize)
- SOC 681: Mixed Methods (Jill Suitor)
- SOC 681: Event History Analysis (Hui (Cathy) Liu)
- STAT 511: Statistical Methods (Tonglin Zhang, Yuan Qu, Chong Gu, Boran Gao)
- STAT 512: Applied Regression Analysis (Tiantian Qin)
- STAT 519: Introduction to Probability (Yuan Gao, Anirban Dasgupta)
- STAT 524: Applied Multivariate Analysis, Lingsong Zhang
- STAT 656: Bayesian Data Analysis (Vinayak Rao, Arman Sabbaghi)
- ASEC 582: Introduction To The Application Of Inferential Statistics (Rama B Rashakrishna)
- CS 573: Data Mining (Rajiv Khanna)
- CS 578: Statistical Machine Learning (Ruizhe Zhang)
- EDCI 615 – Qualitative Research Methods in Education (Nadine Dolby)
- EDCI 616 – Qualitative Data Collection& Analysis (Steven Burdick)
- EDCI 684 – AI & Qualitative Research (Stephanie Zywicki)
- HIST 610 – Theory & Methods (Andrew Bellisari)
- TECH 697: Qualitative Research Methods for Technology Studies (Paul Parsons)
Grants
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.