JSM 2005 Online Program

Abstract #304227

This is the preliminary program for the 2005 Joint Statistical Meetings in Minneapolis, Minnesota. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 7-10, 2005); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

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Activity Number:	136
Type:	Contributed
Date/Time:	Monday, August 8, 2005 : 10:30 AM to 12:20 PM
Sponsor:	Section on Bayesian Statistical Science
Abstract - #304227
Title:	Contextual Effects in Ecological Inference
Author(s):	Ying Lu*+ and Kosuke Imai
Companies:	Princeton University and Princeton University
Address:	284 Walalce Hall, Princeton, NJ, 08540, USA
Keywords:	cross level inference ; Bayesian method ; missing data problem
Abstract:	Most existing models of ecological inference, such as Goodman's ecological regression and King's EI model, assume independence between the contextual variables (e.g., income and education) and the unknown variables (e.g., voter turnout). However, when this assumption is violated, the resulting estimates will be biased. In this paper, we first extend the parametric model of Imai and Lu (2004) to account for the contextual variables. In particular, we model the unknown variables jointly with the observed contextual variables subject to the deterministic bounds condition. The advantage of this approach is that it can be extended readily to the nonparametric model. Simulation studies and an empirical example are given in order to evaluate the model performance after incorporating the contextual variables in different scenarios.

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