Workshop in Methods

Permanent link for this collectionhttps://hdl.handle.net/2022/18413

The Workshop in Methods (WIM) was created in 2009. The initial idea for WIM began with Scott Long, who discussed his vision with Dr. William Alex Pridemore. Pridemore created WIM and directed the series until 2013. The mission of the Workshop in Methods is to provide introductory education and training in sophisticated research methods to graduate students and faculty in the social sciences at Indiana University. Our goal is to supplement statistics and methods courses across the Bloomington campus with topical workshops led by leading methodological scholars from IU and across the United States. In Fall 2013, the SSRC, working under the direction of the WIM advisory committee, began hosting the WIM series.

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Now showing 1 - 20 of 129

Abortion Attitudes: The difficulties of simple questions about complex issues
(Indiana University Workshop in Methods, 2022-08-26) Jozkowski, Kristen; Crawford, Brandon
The recent Supreme Court decision in the Dobbs v. Jackson resulted in the overturning of Roe v. Wade, ending the constitutional right of a pregnant person to choose to have an abortion until fetal viability (i.e., until about 24 weeks). Although this ruling marks a significant shift in abortion policy and climate in the U.S., the vast majority of polls measuring abortion attitudes show that there has been little change in attitudes since the 1970s. What does that mean about the relationship between policy and public opinion and how we measure abortion attitudes? In this workshop, we will provide an overview of abortion as a contentious social issue, historical trends of abortion attitudes, and the implications of the Dobbs v. Jackson decision. Next, we will share an overview of our project: Developing and Assessing Measures for Social Surveys (DAMSS). Then we will present some of our preliminary findings and discuss what makes a “good” question actually a “bad” question? We will conclude with what these preliminary findings mean for how we assess abortion attitudes and what the DAMSS project will be doing next. No previous experience with abortion attitudes is needed. Although the focus of this presentation will be abortion attitudes, the findings and methodology have relevance for other social issues.
Accessing Complex Systems: An Introduction to Agent-Based Models
(Indiana University Workshop in Methods, 2020-03-06) Uribe-McGuire, Alicia
The world we live in is complex. Individuals change, evolve, and grow as they experience the world and others around them. Agent-based and computational models can help us account for the complexity and dynamics of interactions among individuals. This seminar will include an introduction to agent-based models, explore some prominent examples, and provide a brief primer on how to approach these models.
Advanced Topics in R
(Indiana University Workshop in Methods, 2014-12-05) Davis, Jefferson; Zhang, Hui; Michael, Scott
In this follow up workshop to “Introduction to R” researchers will have the opportunity for a deeper dive into R. Available on all IU's supercomputers, R is a flexible open source statistical programming language that can work with large and complex data sets. This workshop will address several advanced topics in R as well as giving participants the opportunity to use R on IU’s supercomputers. The topics to be covered include: R scripting on IU supercomputers; debugging, profiling, and performance analysis of R code; parallel programming in R, including the Rmpi and snowfall packages; and advanced plotting in R. Participants will have access to the supercomputer Big Red II during the session and will be able to see hands-on examples of running R code and submitting batch jobs in R.
Analyzing longitudinal changes in mental health: Integrating variable-centered and person-centered approaches
(Indiana University Workshop in Methods, 2022-03-25) Chow, Angela
While variable-centered approaches to data continue to be widely employed in public health, psychology and many other disciplines, the use of person-centered approaches have become increasingly common. A third type of approaches, which integrates both variable- and person-centered approaches, has been rapidly developed and adopted in research which involves longitudinal data. In this workshop, we will first compare these three approaches. Then, drawing on a longitudinal study which examines the trajectory patterns in maternal depressive symptoms across pre- and postnatal periods, we will go through the steps of conducting general mixture modeling, an analytical procedure combining variable- and person-centered approaches. We will also discuss how this integrated approach can help to address research questions which are difficult to answer otherwise.
Analyzing ordinal data with metric models: What could possibly go wrong?
(Indiana University Workshop in Methods, 2018-03-23) Kruschke, John K.
We surveyed all articles in the Journal of Personality and Social Psychology, Psychological Science, and the Journal of Experimental Psychology: General that mentioned the term "Likert," and found that 100% of the articles that analyzed ordinal data did so using a metric model. We demonstrate that analyzing ordinal data as if they were metric can systematically lead to errors. We demonstrate false alarms (i.e., detecting an effect where none exists, Type~I errors) and failures to detect effects (i.e., loss of power, Type~II errors). We demonstrate systematic inversions of effects, for which treating ordinal data as metric indicates the opposite ordering of means than the true ordering of means. We show the same problems --- false alarms, misses, and inversions --- for interactions in factorial designs and for trend analyses in regression. We demonstrate that averaging across multiple ordinal measurements does not solve or even ameliorate these problems. We provide simple graphical explanations of why these mistakes occur. Moreover, we point out that there is no sure-fire way to detect these problems by treating the ordinal values as metric, and instead we advocate use of ordered-probit models (or similar) because they will better describe the data. Finally, although frequentist approaches to some ordered-probit models are available, we use Bayesian methods because of their flexibility in specifying models and their richness and accuracy in providing parameter estimates.
Assuming in Public: Use DAGs to improve transparency and causal estimation
(Indiana University Workshop in Methods, 2024-02-27) Brauer, Jonathan
Scientists routinely make causal inferences – whether implicit or explicit – about correlations generated from statistical analyses of experimental and observational data. However, while theorized causes are usually directionally specific, correlations are inherently symmetric or directionally ambiguous. Moreover, multiple causal structures can produce equivalent correlational results, posing significant threats to the validity of statistical inferences. Fortunately, advances from the “causal revolution” in science and statistics have provided us with powerful tools, such as potential outcomes and directed acyclic graphs (DAGs), to better understand causes and effects. This talk will focus on how DAGs can help us “assume in public” more effectively. By introducing DAGs early in the research workflow and adhering to simple rules for their use, we can formalize the causal assumptions underlying our theories and statistical models, thereby enhancing transparency and reducing avoidable biases in causal estimation. The presentation will cover the four foundational structures in causal systems, as represented in DAGs: complete independence, pipes, forks, and colliders. Real-world and simulated examples – drawn from the speaker’s blog posts – will illustrate key concepts, such as d-separation, “good and bad controls,” and adjustment sets. Finally, the talk will introduce tools and resources to help researchers more confidently and effectively navigate the assumptions and challenges of causal inference.
Beginning Text Analysis with R
(Indiana University Workshop in Methods, 2016-04-29) Gniady, Tassie
R is an open source language for statistical programming and graphics. With libraries oriented towards text mining, and one even called twitteR, using R to analyze social and humanities data has gotten easier than ever. This workshop will introduce some basics of R and guide you through a scaffolded approach to learning R that includes written tutorials, online web apps, dynamic notebooks, and downloadable code. In this session we will generate basic word clouds and cluster dendrograms.
Best Practices in SPSS
(Indiana University Workshop in Methods, 2025-03-07) Klein, Neela; Ray, Elizabeth
SPSS is a common data analysis program for work in Social Sciences. It offers a point of access for data cleaning, description, and analyses in a user-friendly manner. Different from programs like R that require coding, SPSS provides a “point and click” interface that allows you to use the program intuitively. Behind the scenes of this “point and click” interface, though, SPSS can provide, generate and execute code FOR YOU, making it an accessible option for researchers aiming to improve transparency and replicability of their analyses. SPSS is a powerful and approachable tool for anyone looking to view, describe, clean, edit, or analyze data with simple to complex statistical analyses. The goal of this workshop is to provide an accessible, applied, and practical understanding of how to use SPSS. The workshop will begin with a description of the software including a detailed map of how to interact with the software, how to view previously collected data, how to subsect data and create composite variables, and how to create both descriptive visuals of data. We will cover how to execute and interpret various statistical analyses (e.g. ANOVAs, correlations, and regressions). The workshop will include both the point and click method of interacting with SPSS as well as cover how to generate and work with syntax (i.e. SPSS code). Though not required, to make the most of your attendance, arrive with the SPSS software (provided for free for IU faculty, students, and staff) already downloaded.
Black Professionals at Work: Methodological Approaches for Studying an Underrepresented Population
(Indiana University Workshop in Methods, 2018-02-16) Wingfield, Adia Harvey
Adia Harvey Wingfield is Professor of Sociology at Washington University in St. Louis. She specializes in research that examines the ways intersections of race, gender, and class affect social processes at work, and is an expert on the workplace experiences of minority workers in predominantly white professional settings, and specifically on black male professionals in occupations where they are in the minority. Prior to her talk at the Workshop in Methods, Dr. Wingfield will speak at the Karl F. Schuessler Institute for Social Research (1022 E. Third St.) on "Professional Work in a ‘Postracial' Era: Black Health Care Workers in the New Economy," 12-1:30pm.
A Brief Introduction to Multilevel Modeling: Concepts & Applications
(Indiana University Workshop in Methods, 2015-02-27) Rutkowski, Leslie
In this two-hour workshop, participants will be provided with a brief overview of multilevel modeling concepts and several applications, including random intercepts and random slopes models. Several examples will be provided along with SAS syntax and a data set will be made available. Participants will have an opportunity to fit several models in SAS and interpret the results.
Causal Inference for Complex Observational Data
(Indiana University Workshop in Methods, 2019-09-20) Huber, Chuck
Observational data often have issues which present challenges for the data analyst. The treatment status or exposure of interest is often not assigned randomly. Data are sometimes missing not at random (MNAR) which can lead to sample selection bias. And many statistical models for these data must account for unobserved confounding. This talk will demonstrate how to use standard maximum likelihood estimation to fit extended regression models (ERMs) that deal with all of these common issues alone or simultaneously.
Challenges and Opportunities when Studying Hard-to-Reach Populations
(Indiana University Workshop in Methods, 2022-02-25) Chong, Chinbo
Are you interested in surveying hard-to-reach populations? In this talk, I will briefly discuss my book project and ongoing projects, focusing on my motivations for providing practical tips for collecting survey data among Asian Americans and Latinos. I will emphasize the challenges of studying hard-to-reach populations like Asian Americans and Latinos. In that spirit, I will introduce considerations and practical steps for pursuing research from sampling strategy, matching process, survey questionnaire ordering, the timeline for completing your project, to various negotiation stages to consider when working with a survey firm. Finally, I will offer limitations of this approach and how you might address them in the publication of your research.
Characters and Grammar: How Linguists Can Become More Fluent in R
(Indiana University Workshop in Methods, 2022-09-23) Myers, James
R is not just statistics software, but a full-fledged computer language, and with its thousands of extra packages linguists can program it to do things far beyond basic statistical analysis and graph-making (though of course R is great at those things too). In this talk I hope to give a painless introduction to the grammar of R for those who have not yet dared to try it, while still offering some new ideas to more experienced users. The empirical focus is on my own explorations of the “grammar” of Chinese characters, which will allow me to survey a variety of methods of particular use to Chinese linguists, including how to work with non-Roman writing systems, how to analyze text corpora, how to compile data from lab experiments, and of course how to run statistical analyses and make graphs, from the simple to the fancy, including new types of analyses that you can invent yourself with some basic concepts in probability and a bit of programming. If time permits, I will also demonstrate how diverse and powerful R’s extra packages really are by highlighting tools for sound and image processing (the latter useful for the study of writing systems and sign language). Above all, I will emphasize that there is no reason to feel intimidated: anybody can become ever more fluent in R through workshops like these, textbooks, internet searches, and most importantly, patient trial and error.
Correspondence Audits: Design Issues and Practical Examples
(Indiana University Workshop in Methods, 2018-09-07) Gaddis, S. Michael
During the past decade, field experiments in the social and behavioral sciences have gained in popularity as the internet has made implementing experiments easier, cheaper, and faster. However, although researchers may have a conceptual knowledge of how experiments work, the actual experience of implementing a field experiment for the first time is often frustrating and time consuming. Researchers without prior experience often struggle with a number of issues such as navigating IRB, obtaining true random sampling and assignment, understanding blocking, and interpreting different types of treatment effects. The initial learning curve may be steep but the rewards are plentiful as experiments produce highly valued original data, lend themselves to causal analysis in ways that traditional survey data cannot, and become easier to implement as a researcher’s experience level increases. This talk will introduce social scientists to the basics of a particular type of field experiment -- the correspondence audit -- and walk through a number of design issues that first time users often struggle with. Dr. Gaddis will provide practical examples from his own and others' work to illuminate some of the pitfalls of this method and help the audience gain confidence in embarking on their own field experiments.
Covering the 2020 Election and the Lessons of 2012 and 2016
(Indiana University Workshop in Methods, 2019-10-04) Bump, Philip
Philip Bump is a National Correspondent for the Washington Post.
Cycles of Conflict, a Century of Continuity: Computational Methods and the Longue Durée
(Indiana University Workshop in Methods, 2022-09-09) Nelson, Laura K.
The women’s liberation movement hotly debated both the cause of women’s oppression and the best approach to changing it. When treated as a moment within 1960s political polarization, these debates can seem esoteric and arbitrary. When examined across the longue durée, I show that these debates reflect complex and stable differences in interpretation that were tied to place more than to the political moment. Using computational methods to examine women’s movements from the 1860s to the 1970s, I challenge long-standing theories of feminist waves and reflect on the potential for using computational methods, in particular when combined with qualitative methods and interpretation, to re-examine historical patterns in social movements over long time frames.
Decolonial Ethnographic Approaches to Social Justice Research
(Indiana University Workshop in Methods, 2021-03-26) Martinez-Rivera, Mintzi
Dr. Mintzi Auanda Martínez-Rivera is an Assistant Professor of Anthropology in the Department of Sociology and Anthropology at Providence College. She has a dual PhD (Folklore and Anthropology) from Indiana University-Bloomington (IUB). Her research and teaching focuses on P’urhépecha culture, indigenous youth culture, indigenous popular culture, expressive cultural practices, Critical Indigenous and Anti-Oppressive research methods, and cultural transformations. She has published on the indigenous rock movement in Mexico, about P’urhépecha wedding rituals, and on conducting research in conflict zones and research methodologies. In June 2021, her co-edited volume with Dr. Solimar Otero Theorizing Folklore from the Margins: Critical and Ethnical Approaches will be published by Indiana University Press, and she is currently working on her book manuscript, tentatively titled Getting Married in Angahuan: Creating Culture, Performing Community. She is also currently co-editing, together with Drs. Solimar Otero and Rachel V González, a special volume on Latinx Folkloristics: Transnational WOC Perspectives for the Journal of American Folklore. For the last 2 years she has cooperated with the Social Justice Collaborative, a non-profit organization in California that provides legal aid on immigration cases.
Difference-in-Differences with Staggered Treatments: An Application with Firms and Revolving Door Lobbying
(Indiana University Workshop in Methods, 2021-09-03) McCrain, Josh
“Revolving door” lobbying describes the back-and-forth transition of individuals between public service and employment in lobbying, raising normative concerns around the role of special interests in public policy. Little, however, is known about individuals who make the transition from lobbying into government. Using unique panel data from 2001-2020 of U.S. federal bureaucrats and congressional staff matched to lobbying records, we 1) provide important stylized facts on this phenomenon and 2) quantify the value to lobbying firms when their employees enter government service. Employing a matched difference-in-differences design appropriate for staggered treatment timing, we find lobbying firms that gain government connections through departure of one of their lobbyists experience a 36% revenue increase, or roughly $320,000 per year. These results shed light onto the political economy of the lobbying industry and the value of access in lobbying, and provide needed context surrounding ongoing policy debates on revolving door regulation.
Documenting Quantitative Research for Transparency and Reproducibility: Principles and Standards
(Indiana University Workshop in Methods, 2018-01-26) Ball, Richard; Medeiros, Norm
This talk will present a set of standards for the replication documentation (data, code, and supporting information) that authors should assemble and make public when they release studies reporting the results of research based on analysis of statistical data. We will begin from first principles: What purposes is replication documentation intended to serve? And what must be true of the contents and organization of the documentation for a study if it is to fulfill those purposes? We will then describe how these general principles are embodied in the particular documentation standards we propose. Further discussion will include: (i) a comparison of our proposed standards with existing guidelines, such as TOPS, DA-RT, the BITSS Manual, and the "data policies" that have been adopted by a number of prominent journals, (ii) using the Open Science Framework (OSF), an on-line file management platform, for assembling and sharing replication documentation, and (iii) the curricular resources that are being produced by Project TIER for teaching and learning reproducible research methods.
The Ethics of Naming and the Perils of Masking in Ethnography
(Indiana University Workshop in Methods, 2015-12-11) Jerolmack, Colin
Ethnographers routinely employ pseudonyms and even mask the sites (e.g., street corner, neighborhood, city) of their research. This is usually justified as an ethical necessity, to protect our participants. In this talk, drawing from a paper I am co-authoring with Alexandra Murphy (Michigan), I challenge this justification and spell out some of the ways that masking can potentially harm research participants and impede social science research. Regarding ethics, I show, on the one hand, how masking often fails to provide the guaranteed degree of identity protection and, on the other hand, how research participants may have a very different understanding of what the researcher owes them that has little to do with whether or not they are named (e.g., portraying them as a human, not just a social type). Regarding scientific integrity, I argue that masking reifies ethnographic authority, invokes a pseudo-generalizability that downplays the particularities of the case (e.g., "Middletown"), and inhibits replicability (or "revisits"), falsifiability, or comparison. I conclude by arguing that masking is a convention, not an ethical or IRB necessity, and while I concede that there are many cases in which masking is the ethical choice, I contend that we should no longer consider it the default option.

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