Thursday, September 28, 2017

Modeling Enthusiasm

One day this past summer, a Summer Program participant in need of help showed up to Samantha Marinello and Rachel Nordgren’s office hours. “He was trying to do this complicated thing with his own data. It was a question of fixing code,” says Nordgren, who was a teaching assistant, along with Marinello, for Longitudinal Analysis. The participant was clearly frustrated. Marinello and Nordgren worked with the participant until, finally, he got the program to run and produce output. To their surprise, he started cheering. In the library.

The teaching duo’s longitudinal workshop was filled with other equally enthusiastic participants. “We had a loyal core that spent a fair amount of time at office hours,” says Nordgren. Among these regular attendees were a few individuals seeking more than guidance on a class assignment. Nordgren mentions one “awesome” participant. “Not only did she want to know what she was doing, but she wanted to figure out how think about it, and how to translate what she was seeing into her own research.”

Another participant wanted to understand what was going on with the models. He seemed compelled by the question, “How does this all fit together?” “There was one day he came to office hours, and no one else came, so we just ended up talking for two hours about sampling distribution and the central limit theorem,” says Marinello. “It was fun talking to him, and you could tell that things were clicking together.”

“If your students are not excited and don’t care, it is so much harder to be enthusiastic yourself,” says Nordgren, a PhD student in biostatistics at the University of Illinois at Chicago. Prior to working at the Summer Program, she’d been a research assistant in her department, but never a TA. Teaching experience was a must, Nordgren’s advisor had informed her, if she intended to pursue a career in academia. Rather than be a TA in her department for a mandatory intro stats course, Nordgren applied for a “TAship” at the Summer Program, which she’d heard about from Michael Berbaum, a UIC professor with whom she’d conducted research. “This seemed like a cool way to actually have a chance to be with people who are motivated to learn, and get exposed to how social science thinks about stats,” Nordgren says.

Samantha Marinello (pink shirt) and Rachel Nordgren (far
right) in the workshop "Longitudinal Analysis."
This was also Marinello’s first time as a TA, although she’d had prior experience tutoring students. “I thought it would be a really good opportunity to teach, because you really have to know the material to be able to teach it,” she says. A PhD student in health policy at the University of Illinois at Chicago, Marinello was energized by her meetings with participants. “They asked really deep, very good questions, and on top of that, we got to know the students,” she says. “Outside of helping them with assignments or going over material with them in class, I got to talk to students who were applying to PhD programs.” She shared her experiences and knowledge about things like writing a statement of purpose and switching advisors.

The TA job was not without its challenges, such as finding more than one way to explain the interpretation of a nonlinear model to a participant. “Being a TA for the first time, you have to learn there are times you don’t know the answer,” says Marinello. “And that’s hard to deal with. Sometimes it’s not bad, because you’re like, ‘Let me get back to you.’ There have been a couple of times where I’ve sent emails to students later that day, [saying], ‘Here’s a really good full explanation.’”

Marinello and Nordgren’s tireless efforts didn’t go unrecognized by participants. “They’d be excited about understanding something. They were so appreciative,” says Marinello.

“We had a bunch of people make a really big point of thanking us today in the last class,” says Nordgren. “To some of them, I was like, ‘Thank you!’”

An Interview with Alison H. Merrill

Alison H. Merrill is a Ph.D. candidate in the Department of Political Science at Texas A&M University. Alison was a participant in the 2015 Program. In 2017, she worked as a teaching assistant for the Summer Program workshop "Time Series Analysis II: Advanced Topics." For more information about Alison, visit

Can you tell us about your research?
My main research interests focus primarily on American political institutions and decision making, with an emphasis on judicial politics and applications of quantitative methodology to the study of judicial decision making. In particular, my principal research agenda investigates how strategic behavior by litigants and Supreme Court justices influences which cases the Court hears and how they are decided. In my dissertation, I focus on how the Supreme Court's discretion in selecting cases shapes behavior by lower court judges and litigants prior to certiorari in ways that ultimately feed into the Supreme Court's decision-making. I address this issue by considering the Supreme Court's decisions as the results of layers of strategic behavior that should be considered together. The Supreme Court of the United States has substantial discretion over the composition of its docket. Parties must petition the Supreme Court for a writ of certiorari, and four justices must consent for the Court to accept arguments on the merits of a case. This set of institutional arrangements provides ample opportunity for the Court’s justices as well as litigants and lower court judges to act strategically in anticipation of (uncertain) decisions on the merits nested within (uncertain) decisions about certiorari. Although there is a growing recognition among scholars of Supreme Court decision-making of the need to account for pre-certiorari choices in theoretical and empirical models of judicial behavior, the vast majority of research on the topic focuses exclusively on votes and decisions at the merits stage. My work aims to move past these limitations and understand Supreme Court decisions as political outcomes nested in earlier strategic choices made inside and outside the Court.

How did you become interested in this topic?
I have always been absolutely fascinated by the Supreme Court. The Court is hands-down my favorite building in Washington, D.C. and I find learning about the justices' personalities and how they structure the interactions between justices and other members of the government to be interesting and engaging. I remember my mom giving me a copy of The Brethren (Bob Woodward's inside look at the Burger Court) and absolutely devouring the book, and hunting for more information on the justices when I was in middle school. With the same kind of energy, I devoured Jeffrey Toobin's The Nine. However, the research that I got involved in as an undergraduate at Virginia Tech focused more on voting and elections, and the role of young adults in the political process. I applied to grad school with the intention of studying the effect of young adult participation on macro (or aggregate) public opinion. During my first semester at Texas A&M, I was in the American Political Institutions seminar and we were reading McGuire and Stimson's 2004 article "The Least Dangerous Branch Revisited," and was intrigued about their application of aggregate policy mood to understanding and explaining Supreme Court liberalism. It was really the first time that I had seen public opinion and Supreme Court decision making in the same study. I went to my professor, now advisor, Joe Ura, and asked if it would be possible to apply the same framework to Supreme Court affirmances, instead of just reversals (which is what McGuire and Stimson analyzed), and that question lead to our first co-authored project. The more we worked on that paper, the more I read about the Court from a decision making perspective. And I started to want to better understand how the Supreme Court structures their docket, which considerations come into play, whether or not the considerations vary across issue areas, and how other actors (such as litigants, lower court judges, and elected officials) influence the menu of cases that the Court selects from when setting their agenda for any given term. I soon realized that there were not a lot of answers to these questions because the literature on certiorari and the literature on agenda-setting and decision making, while complementary and acknowledging one another, did not actually engage one another theoretically or empirically. Finding that gap helped me to come up with my overall research agenda and dissertation topic.

What has your research revealed?
In one of my dissertation chapters, "Selecting on the Economy? Economic Issues, Public Opinion and the Supreme Court," I consider how changing macroeconomic conditions influence incentives for litigants, lower court judges, and justices to make choices resulting in cases dealing with economic issues decided by the Court. I argue that the various actors' influence on the cumulative process can be parsed, to a limited extent, by the temporal structure of the association between the economy and case production. More proximate economic effects likely act through justices' behavior directly, and longer-lagged economic effects likely act through antecedent actors. I find that higher unemployment is associated with greater attention to the economy in the Supreme Court's docket at multiple lags, indicating economic case selection dynamics among the Court's justices and at preceding stages of the case production process. However, economic growth is significantly associated with attention to the economy at a relatively early lag, suggesting that growth brings cases to the Court via the actions of parties and judges outside the Court.

That litigants are thinking ahead to the decision on the merits when they chose whether or not to appeal their case to the Supreme Court is pretty cool! And in my other two dissertation chapters, I seek to better explain the mechanisms that help to structure the choices and decisions made by the litigants across issue areas.

What do you hope to accomplish with your work and research? 
Honestly, I am just so excited about the opportunity to contribute to the conversations that exist in Law&Courts concerning our understanding of the decision making process. I hope that my research helps to advance our understanding of the certiorari process and how the earlier actions taken by and decisions made by external actors influences the justices' decisions to hear cases in the first place and then the decision issued by the Court. One of my goals post-dissertation is to expand the data collection that I am currently engaged in, and create a database on certiorari that people can use in their own work. In this database, I hope to have information from the U.S. Courts of Appeals on the cases that were eligible for review by the Supreme Court, which cases were appealed, when that appeal was initiated, the issue area of the case, whether it was heard by a 3-judge panel or en banc (by the full bench, or all judges appointed to that circuit court), and whether or not the appeal was granted review by the Supreme Court. Having this information available, and in one location will greatly assist other scholars with their own research on the Supreme Court's decision making processes.

Who had the biggest influence on your career path?
The person who has had the biggest influence on my career path is my former undergraduate advisor, the late Dr. Craig L. Brians. It was Dr. Brians who first introduced me to quantitative methods and how you could use these methods to explain and predict political behavior. He was the one who brought me on to his undergraduate research team, mentored me through Master's-level coursework at Virginia Tech, and suggested I apply to graduate school. I definitely would not be where I am today without his guidance, optimism, and unfailing support and encouragement.

Sadly, Dr. Brians passed away unexpectedly in the fall of my first year at Texas A&M. It was, and still is, incredibly difficult knowing that he is no longer with us. I know this next part is going to sound a little cheesy, but it is the truth, so here it goes! However, with every milestone I hit in my graduate education (successfully completing my first year, passing my comprehensive exams, defending my dissertation prospectus, teaching my own class for the first time, and eventually defending my dissertation and (hopefully) getting a job), I know that he would be incredibly proud. I have honestly tried to work hard for his memory. To show him that his good faith and trust in me is being rewarded, and to become the scholar, researcher and teacher he believed that I could be.

How did you become a TA for the Summer Program? 
I was fortunate enough to become a TA for the Summer Program because of my experience as a participant. I remember talking to Sandy towards the end of the 2015 Summer Program and telling her that this was some of the most fun that I had ever had, while simultaneously being incredibly challenging. And that if she could use my help in the future, I would be beyond happy to come back. Thankfully, Texas A&M provides a rather rigorous and comprehensive Methods program for their grad students, and three of my colleagues had previously been TAs for the Summer Program (Clay Webb, Soren Jordan, and Andy Philips), so my background was well known. I was asked to TA for the 2016 Summer Program, but was unable to come because I got married that summer right in the middle of the two sessions. I kept in touch with Sandy, and let her know that I would be thrilled to have the opportunity to work as a TA for the 2017 session if she could find a place for me. Thankfully, I was asked to TA for Advanced Time Series by Paul Kellstedt (one of my advisors at A&M) and Mark Pickup. And hopefully, I'll be able to come back next summer as well!

What moment at the Summer Program stands out as the most memorable?
There are a couple of moments about the Summer Program that stand out as memorable, and I think that is one reason why the Summer Program is so successful and people love to come back any way that they can. As a participant, I made some amazing friends from all over the country, and we're still in touch! We make it a point to meet up at conferences whenever we can, and we share our research papers with one another to get feedback, talk about different applications of methods, and just provide one another with so much support. And as a TA, I have only increased that network, which is so amazing! Additionally, the Blalock Lectures really stick out to me. They cover a wide range of topics and are examples of how to be a good member of the discipline, effectively teach statistics, and effectively use and present different methodological approaches. I still reference notes I took during the Blalock Lectures I attended in 2015. It's such an amazing resource for the participants, TAs and instructors during the Summer Program. And, seeing Bill and Sandy's beautiful dalmatians at the picnics is pretty memorable as well! I have a dog who I absolutely adore! So, it's really hard to be apart from him while I'm at the Summer Program, and getting a chance to get my puppy fix is a definite plus!

Tuesday, September 19, 2017

Mark your calendars!

We're happy to announce the dates for our 2018 Four-week Sessions:

First Session: June 25 - July 20, 2018
Second Session: July 23 - August 17, 2018

Additionally, we will offer many 3- to 5-day workshops in Ann Arbor and other locations across the country. These short workshops will be held from May through August 2018.

We will post our complete course schedule in January 2018. Official registration for all 2018 courses will open in early February 2018.


Wednesday, August 16, 2017

The 2017 Summer Program comes to an end

From May through August, nearly 1,000 participants attended more than 80 courses offered in 8 cities across the U.S., Canada, and Europe.

Our participants came from more than 30 countries and represented more than 30 disciplines. We greeted many familiar faces and welcomed many more new participants.

Our phenomenal instructional staff included more than 100 instructors and TAs.

Thanks to everyone who joined us!


Monday, June 19, 2017

Free Workshop on the 2014 Survey of Income & Program Participation (SIPP)

Led by experts from the U.S. Census Bureau, this workshop will introduce participants to the use of microdata from the re-engineered 2014 "Survey of Income and Program Participation (SIPP)" and provide hands-on applications to prepare them to conduct their own SIPP-based research project.

The SIPP is a panel survey containing detailed measures of employment, health insurance, disability, child care, wealth and assets, program participation, and other topics. It is used to estimate the effectiveness of existing federal, state, and local programs; to estimate future costs and coverage for government programs, such as the Supplemental Nutrition Assistance Program (SNAP, formerly food stamps); and to provide improved statistics on the distribution of income and measures of economic well-being in the country.

Workshop dates and location: September 18-21, 2017 in Washington, D.C.
Application deadline: July 31, 2017


Thursday, April 6, 2017

The 2017 ICPSR Summer Program schedule is now available and registration for the 2017 ICPSR Summer Program is open!

Please check the 2017 ICPSR Summer Program schedule for a complete listing of this year’s courses in both the four-week sessions and the short workshops. If you have any questions about the 2017 Summer Program, send an email to

We also invite you to watch this recorded webinar introducing the Summer Program, our courses, scholarships, and visitor information.

Or, feel free to contact the ICPSR Summer Program directly.


Wednesday, April 5, 2017

Save hundreds of dollars on your 4-week session registration fees!

We offer an early payment discount on registration fees for our four-week sessions. In order to receive this discount, your registration fees must be paid in full before midnight (EDT), April 30, 2017. Beginning on May 1, the registration fees for our First and Second Sessions will increase.

Visit our Registration page for a full list of fees and discounts.