Pre-Conference Reception
Time: April 22, Thursday, 8-11 pm
Location: Michigan League, second floor

Day One (April 23, Friday, ISR 6050)

Welcome Remarks (9:10)
David Featherman, University of Michigan

Session 1 (9:20-10:10): Age, Period, and Cohort Analysis
Chair: Hiroshi Ishida, University of Michigan
Christopher Winship and David Harding, Harvard University. “A General Strategy for the
Identification of Age, Period, Cohort Models: A Mechanism Based Approach.”
Kenneth Land and Yang Yang, Duke University. “Some New Developments in Age-Period-
Cohort Analysis.”

Session 2 (10:20-12:00) Survey Methodology
Chair: Jim Lepkowski, University of Michigan
Kristen Olson and Andy Peytchev, University of Michigan. “Interviewer Experience and Interview Behaviors.”
Andy Peytchev, University of Michigan. “Web Survey Design: Relationship Between Context
Effects and Measurement Error.”
Sonja Ziniel, University of Michigan. “Using Interviewer Observations as Predictors of
Contactability in Face to Face Surveys: A Cross-Country Comparison.”
Ben Hansen, University of Michigan. “Flexible matching in sample surveys containing quasi-
experiments.”

Lunch (served, 12:00-1:20)

Session 3 (1:20-3:30): Causal Inference I (Discussions)
Chair: Christopher Winship, Harvard University
Jennifer Barber, Susan Murphy, and Natalya Verbitsky, University of Michigan. “Adjusting for
Time-Varying Confounding in Survival Analysis.” Discussants: Zhen Zeng and Tony Perez, University of Michigan.
Thomas DiPrete, Duke University. “Assessing Bias in the Estimation of Causal Effects:
Rosenbaum Bounds on Matching Estimators and Instrumental Variables Estimation with
Imperfect Instruments.” Discussants: Emily Greenman and Doug Corey, University of Michigan.
Qi Long, Roderick J. Little, and Xihong Lin, The University of Michigan. “Causal Inference in
Hybrid Intervention Trials Involving Treatment Choice.” Discussant: Colter Mitchell, University of Michigan.

Coffee and refreshment break (3:30-4:00)

Session 4, Public Lecture (4:00-5:30)
Chair: Roderick Little, University of Michigan
Otis Dudley Duncan Lecture by Leo Goodman, University of California-Berkeley. “Three
Different Ways To View Cross-Classified Categorical Data: Rasch-Type Models, Log-
Linear Models, and Latent-class Models.”
Discussants: Mark Becker, University of Minnesota; Yu Xie, University of Michigan

Conference dinner at the Michigan League (6:30-9:00pm)

Day Two (April 24, Saturday, ISR 6050)

Session 5 (9:00-11:10): Causal Inference II (Discussions)
Chair: Ken Bollen, UNC-Chapel Hill
Christopher Winship, Harvard University. “The Estimation of Counterfactual Causal Effects with
Longitudinal Data.” Discussant: Susan Murphy, University of Michigan.
Ken Frank, Michigan State University. “Indices for the Robustness of Causal Inferences for the
Counterfactual.” Discussants: Zhen Zeng and Haiyan Zhu, University of Michigan.
Guanglei Hong and Stephen W. Raudenbush, University of Michigan. "Estimating the causal
effects of grade retention in elementary schools: A tricky problem in multilevel causal
analysis." Discussants: Julia Parkinson and Jessaca Spybrook, University of Michigan.

Session 6 (11:20-12:20): General Issues
Chair: Susan Murphy, University of Michigan
Yu Xie, University of Michigan. “Three Basic Principles of Social Science Research.”
Tim Liao, University of Illinois. “Beyond the Gini: Assessing Inequality with Model-Based
Clustering.”

Lunch (served on site, 12:20-1:30)

Session 7 (1:30-3:30): New Statistical Models and Methods
Chair: Raymond Wong, University of California-Santa Barbara
Ken Bollen, UNC- Chapel Hill. “Latent Variable Models Under Misspecification: Two Stage
Least Squares (2SLS) and Full Information Maximum Likelihood (FIML) Estimators.”
John Fox and Robert Andersen, McMaster University. “Effect Displays for Polytomous Logit
Models: New Results.”
Kazuo Yamaguchi, University of Chicago. “Some Alternative Methods for Modeling the Stability
of Attitude for a Dichotomous Dependent Variable.”
Guang Guo and John Hipp, UNC-Chapel Hill. “A Longitudinal Analysis for Continuous Outcome: Random Effects Models and Latent Trajectory Models.”