The Workshop in Methods (WIM) was created in 2009 with the mission of providing introductory education and training in sophisticated research methods to graduate students and faculty in the social sciences at Indiana University. 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.
Browse workshops from the 2012-2013 academic year below. All of the workshop videos have also been compiled in a playlist on Media Collections Online.
Friday, September 7, 2012
Principles of Workflow in Data Analysis
Dr. J. Scott Long
9:00-11:30am, Indiana Memorial Union Dogwood Room
The workflow of data analysis encompasses the entire process of scientific research: Planning, documenting, and organizing your work; creating, labeling, naming, and verifying variables; performing and presenting statistical analyses; preserving your work; and (perhaps, most important) producing replicable results. Most of our work in statistics classes focuses on estimating and interpreting models. In most “real world” research projects, these activities involve less than 10% of the total work. Professor Long’s talk is about the other 90%. An efficient workflow saves time, introduces greater reliability into the analysis, and generates replicable results. A recent entry on a blog discussing Professor Long’s recent book, The Workflow of Data Analysis Using Stata, claimed: “The publication of [this book] may even reduce Indiana’s comparative advantage of producing hotshot quant PhDs now that grad students elsewhere can vicariously benefit from this important aspect of the training there.” Can you afford to miss this talk?
Dr. Longreceived his PhD in Sociology from Cornell. He is Distinguished Professor and Chancellor's Professor of Sociology and Statistics at Indiana University, Bloomington. He teaches quantitative methods both at Indiana University and at the ICSPR Summer Program. His earlier research examined gender differences in the scientific career. In recent years, he has collaborated with Eliza Pavalko, Bernice Pescosolido, John Bancroft, Julia Heiman and others in studies of health and aging, stigma and mental health, and human sexuality.
Materials available by email (event flyer, presentation slides)
Video [2010 version] (Media Collections Online)
Friday, September 14, 2012
The Mortality Penalty of Incarceration: Evidence from a population-based case-control study of working-age males
Dr. William Alex Pridemore
12:00-1:30pm, Schuessler Institute for Social Research Stryker Room (Room 100)
Dr. Pridemoreis Professor at Indiana University, where he is also Director of the Workshop in Methods. The focus of this presentation is not methods. However, the presenter is the WIM Director and it employs case-control data, so please feel free to attend! The Schuessler Institute is the red brick building at the corner of Third and Hawthorne, across from Memorial Hall.
Sunday, September 16, 2012 and Sunday, September 23, 2012
Introduction to R (Parts I and II)
Thomas Jackson
12:00-2:00pm, Wells Library 402
R is a free statistical programming language that provides many powerful tools for visualizing and analyzing data. R is used by statisticians around the world and is becoming increasingly popular in a variety of quantitative disciplines. R is used exclusively with programming syntax (i.e. no "point-and-click" interface) and therefore has a steep learning curve for new programmers.This four-hour workshop (split into two sessions) will introduce the fundamentals of R. During the first session, participants will become familiar with the R user environment, basic data structures, and syntax. Additionally, methods for creating and importing data files and downloading and using additional packages will be covered. The second session will mainly focus on statistical topics: plotting data, computing descriptive statistics, and performing elementary statistical tests. As time permits, additional topics may include the general linear model (Regression and ANOVA) and writing functions.
Registration required, $10 fee. Thomas Jackson is Senior Consultant at the Indiana Statistical Consulting Center.
Wednesday, September 26, 2012, and Wednesday, October 3, 2012
Equipping Your Statistical Toolbelt (Parts I and II)
Stephanie Dickinson
5:30-7:30pm, Wells Library 503
This four-hour workshop (split into two sessions) will give an overview of the most common data analysis tools used in academic research. We will identify which tool should be used for each job, depending on the types of data and the types of research questions you might come across in your career. Analysis methods to work through will include descriptive stats, percentages, t-test, ANOVA, Repeated Measures, Regression, Correlation, Chi-square tests, and more. Examples will be done together in SPSS software as one of the most common and user-friendly statistical software packages. References will also be made to SAS, R, and Stata.
Registration required, $10 fee. Stephanie Dickinson is Senior Consultant at the Indiana Statistical Consulting Center.
Friday, October 5, 2012
Introduction to Bayesian Data Analysis
Dr. John K. Kruschke
2:00-4:00pm, Ballantine Hall 006
This workshop introduces you to Bayesian data analysis, hands on. Intended audience is graduate students and others who want a ground-floor introduction to Bayesian analysis. No mathematical expertise is presumed. Complete computer programs will be provided free: find installation instructions and more information about the workshop before arriving. You do not need to bring a notebook computer to the workshop, but you are invited to bring one so that you can run the programs and see how their output corresponds with the presentation material. The two-hour workshop will rocket through the following topics, allocating about a half hour to each. Why you should be embarrassed to report p values and why you should be proud to do Bayesian analysis. Bayes' rule, grid approximation, and R. Markov Chain Monte Carlo and BUGS. This does not involve any physical restraints or insects. Unfortunately it also does not involve Monte Carlo. Linear regression. If time: Hierarchical models. But there won't be time. So you'll have to take the course or read the book.
Dr. Kruschke is five-time winner of Teaching Excellence Recognition Awards from Indiana University, where he is Professor of Psychological and Brain Sciences, and Adjunct Professor of Statistics. He has written an introductory textbook on Bayesian data analysis; see also the articles linked above. His research interests include models of attention in learning, which he has developed in both connectionist and Bayesian formalisms. He received the Troland Research Award from the National Academy of Sciences.
Materials available by email (event flyer, presentation slides)
Video (Media Collections Online)
Friday, October 19, 2012
How to Design Effective Web Surveys
Kevin Tharp, Lilian Yahng, and Ashley Bowers
12:00-1:30pm, Woodburn Hall 120
The past decade has witnessed an explosion in the use of web surveys to collect scientific data in education, health and medicine, business and public policy, and the social sciences. Web surveys have brought exciting new capabilities that expand what we are able to do as survey researchers and have provided features that can improve efficiency and data quality. Yet, they also present new challenges in survey design and usability and must keep pace with rapidly changing technology. In this workshop, we will provide practical guidance on how to effectively lay out and design web surveys and implement them to maximize response rate and data quality. We will show examples of available features for designing, administering, and analyzing web surveys using off-the-shelf and custom survey systems.
Kevin Tharp is Director of Technologies at IU’s Center for Survey Research. Lilian Yahng is Director of R&D and the Research Laboratory at IU’s Center for Survey Research. Ashley Bowers is Clinical Assistant Professor in the School of Public and Environmental Affairs at Indiana University, where she is also Director of the Center for Survey Research.
Materials available by email (event flyer, presentation slides)
Video (Media Collections Online)
Friday, October 26, 2012
A Practical Guide to Generating and Analyzing Political Event Data
Dr. Philip Schrodt
2:00-5:00pm, Woodburn Hall 101
Political event data – categorical data on who did what to whom – is now being coded in near real time using open source software. This talk will look at some of the data sets that have recently become available, then consider the practical issues involved in doing customized coding, with a focus on the TABARI coding system and other tools developed at Penn State. Topics will include text filtering and formatting, named-entity recognition, the TABARI verb phrase and noun phrase dictionaries, and the CAMEO event and actor coding schemes. The talk assumes a general familiarity with social science data but otherwise has no prerequisites. Background information on the Penn State event data project can be found at http://eventdata.psu.edu.
Dr. Schrodt is Professor of Political Science at Pennsylvania State University. He received an M.A. in mathematics and a Ph.D. in political science from Indiana University. Prior to coming to Penn State in 2010, he taught for 21 years at the University of Kansas and 11 years at Northwestern University, where he helped develop Northwestern's programs on mathematical methods in the social sciences. Dr. Schrodt's major areas of research are quantitative models of political conflict and computational political methodology. His current research focuses on predicting political change using statistical and pattern recognition methods, research that has been supported by the National Science Foundation, the Defense Advanced Research Projects Agency, and the U.S. government's multi-agency Political Instability Task Force.
Materials available by email (event flyer, presentation slides)
Video (Media Collections Online)
Friday, November 9, 2012
Crisp and Fuzzy Set Qualitative Comparative Analysis (QCA)
Dr. Peer C. Fiss
1:00-4:00pm, Woodburn Hall 120
Much of current social research deals with complex systems of interdependent factors. Yet, conventional statistical methods are frequently less adept at unpacking these complex interdependencies. The current workshop provides an introduction to Qualitative Comparative Analysis (QCA), a set-theoretic method developed by Charles Ragin that is better suited to the examination of situations where causality is conjunctural, and equifinal (i.e. where different causes may combine to bring about an outcome of interest and where there is more than one path to an outcome). While QCA was initially developed to provide a formal approach for the analysis of medium-N situations (e.g., 12-40 cases), more recently the approach has also been extended to deal with large-N situations (e.g., 100+ cases). The workshop will offer an introduction to the logic of comparative research along with an introduction to the basic concepts of set-theoretic analysis using examples from empirical work employing the fs/QCA software package.
Dr. Fiss is the McAlister Associate Professor of Business Administration at the Marshall School of Business of the University of Southern California. He is broadly interested in how meaning structures shape organizational actions and has studied this in the context of how practices diffuse, how they change, and how accounts framing and justifying practices are constructed. In addition, he has worked on configurational theory using set-theoretic methods such as fuzzy set Qualitative Comparative Analysis (fsQCA).
Materials available by email (event flyer, presentation slides)
Video (Media Collections Online)
Friday, November 30, 2012
An Introduction to Propensity Score Analysis
Dr. Michael Massoglia
2:30-4:30pm, Woodburn Hall 120
This seminar presents a general overview of propensity score modeling. It begins with a basic discussion of the logic and some notable features of the propensity model. Next we formally present propensity models, and discuss the assumptions underlying the approach. From there we move to a discussion of potential strengths and weaknesses of the propensity models, as well as some common issues to consider when using propensity scores in the research process. The presentation next goes step by step through the estimation process, including the use of different matching procedures and the calculation of robustness tests. The presentation concludes with group discussion and questions.
Dr. Massoglia is Assistant Professor of Sociology at the University of Wisconsin. His research focuses on the social consequences of the expansion of the penal system, the relationship between the use of legal controls and demographic change in the United States, and patterns and consequences of criminal behavior over the life course. Current research projects examine historical variation in U.S. criminal deportations as well as the relationship between incarceration and neighborhood attainment and racial composition.
Materials available by email (event flyer, presentation slides, recommended reference)
Video (Media Collections Online)
Friday, December 7, 2012
Multi-Dimensional Scaling: An Introduction
Dr. William G. Jacoby
12:00-3:00pm, Woodburn Hall 120
Would you like to draw pictures of your data in ways that reveal structures not obvious from inspection of the data values alone? Multidimensional scaling (MDS) can accomplish that objective. MDS produces a “map” of stimuli based on information about the “proximities” among them. The stimuli are any objects of interest to the researcher (e.g., presidential candidates for a political scientist, consumer products for a market researcher, occupations for a sociologist), and many types of information can be interpreted as proximities (e.g., correlations, similarity judgments, profile dissimilarities, etc.). MDS methods have many potential applications in empirical research. They can be used to simplify the contents of large complex datasets, model similarities among sets of objects, estimate the cognitive structures underlying survey responses, and optimize the measurement characteristics of qualitative observations. MDS can be generalized to show individual differences across distinct data sources (e.g., subsets of survey respondents or data collected at different time points), and can be adapted to represent respondent preferences among a set of stimuli (i.e., “ideal points” models). This workshop provides an introduction to MDS. It is intended for a general audience and does not assume prior experience with MDS or familiarity with advanced statistical methods beyond basic regression analysis. Specific topics to be covered include: The basic idea of MDS; the general estimation procedure; interpretation of results; different varieties of MDS; and software options for performing MDS analyses.
Dr. Jacoby is Professor of Political Science at Michigan State University. He is also a Research Scientist at the University of Michigan and the Director of ICPSR’s Summer Program in Quantitative Methods of Social Research.
Materials available by email (event flyer, presentation slides)
Videos (Media Collections Online)
Friday, December 7, 2012
The ICPSR Summer Program in Quantitative Methods of Social Research
Dr. William G. Jacoby
3:15-4:00pm, Woodburn Hall 120
Interested in refreshing your quantitative skills or learning a new method that will aid in your research? Whether you are a faculty member or a graduate student, a great place to accomplish both tasks is the Summer Program in Quantitative Methods of Social Research at the Inter-University Consortium for Political and Social Research (ICPSR). ICPSR offers both month-long and 3-5 day short courses. All month-long courses and many of the short courses are offered at the University of Michigan, though several short courses are offered at different institutions throughout the country, including right here at Indiana University (and hosted by WIM!). Who better to provide you information about ICPSR than the Director of the Summer Program himself? Dr. Jacoby will provide a brief description of the ICPSR Summer Program and answer your questions in this hour-long informational session following his WIM presentation on multidimensional scaling. You are welcome to attend both, or only this informational session. Come have all your questions answered by the person who knows more about the Summer Program than anyone else!
Dr. Jacoby is Professor of Political Science at Michigan State University. He is also a Research Scientist at the University of Michigan and the Director of ICPSR’s Summer Program in Quantitative Methods of Social Research.
Materials available by email (event flyer, presentation slides)