DEPARTMENT OF STATISTICS
Statistics Colloquium
University of Connecticut
Storrs, Connecticut
The Department of Statistics Cordially invites you to a Colloquium
Yajuan Si
Assistant Professor
Department of Population Health Sciences
Department of Biostatistics & Medical Informatics
School of Medicine and Public Health
University of Wisconsin-Madison
Bayesian Latent Pattern Mixture Models for Handling Attrition in
Panel Studies with Refreshment Samples
ABSTRACT
Many panel students collect refreshment samples---new, randomly sampled respondents
who complete the questionnaire at the same time as a subsequent wave of the panel. With
appropriate modeling, these samples can be leveraged to correct inferences for biases
caused by non-ignorable attrition. We present such a model when the panel includes many
categorical survey variables. The model relies on a Bayesian latent pattern mixture model,
in which an indicator for attrition and the survey variables are modeled jointly via a latent
class model. We allow the multinomial probabilities within classes to depend on the
attrition indicator, which offers additional flexibility over standard applications of latent
class models. We present results of simulation studies that illustrate the benefits of this
flexibility. We apply the model to correct attrition bias in an analysis of data from the
2007-2008 Associated Press/Yahoo News election panel study.
This is joint work with Jerry Reiter and Sunshine Hillygus at Duke University.
DATE: Wednesday, April 1, 2015
TIME: 4:00 p.m.
PLACE: AUST 105
Coffee at 3:30 in AUST 326