Author's Keywords: duration analysis, selection bias, war participation, leader survival	Convention All Academic Convention can solve the abstract management needs for any association's annual meeting. Submission - Custom fields, multiple submission types, tracks, audio visual, multiple upload formats, automatic conversion to pdf. Review - Peer Review, Bulk reviewer assignment, bulk emails, ranking, z-score statistics, and multiple worksheets! Reports - Many standard and custom reports generated while you wait. Print programs with participant indexes, event grids, and more! Scheduling - Flexible and convenient grid scheduling within rooms and buildings. Conflict checking and advanced filtering. Communication - Bulk email tools to help your administrators send reminders and responses. Use form letters, a message center, and much more! Management - Search tools, duplicate people management, editing tools, submission transfers, many tools to manage a variety of conference management headaches! Click here for more information.
Association: Name: American Political Science Association URL: http://www.apsanet.org
Citation: URL: http://www.allacademic.com/meta/p64619_index.html Direct Link: HTML Code:

Boehmke, Frederick., Morey, Daniel. and Shannon, Megan. "Selection Bias and Continuous-Time Duration Models" Paper presented at the annual meeting of the American Political Science Association, Philadelphia Marriott Hotel, Philadelphia, PA, Aug 27, 2003 <Not Available>. 2009-05-26 <http://www.allacademic.com/meta/p64619_index.html>

Boehmke, F. , Morey, D. S. and Shannon, M. , 2003-08-27 "Selection Bias and Continuous-Time Duration Models" Paper presented at the annual meeting of the American Political Science Association, Philadelphia Marriott Hotel, Philadelphia, PA Online <.PDF>. 2009-05-26 from http://www.allacademic.com/meta/p64619_index.html

Publication Type: Conference Paper/Unpublished Manuscript Review Method: Peer Reviewed Abstract: In this paper we explore the consequences of non-random sample selection for continuous time duration analysis. While the consequences of selectivity are reasonably well-understood in linear regression and common discrete choice models, we have little or no understanding of how selectivity affects duration models. We study this issue by conducting a series of Monte Carlo analyses that estimate common duration models on data that suffer from selectivity. Our findings indicate that the consequences are severe: both coefficients and standard errors may be biased in an unknown direction. In addition, we find that selection bias may create the appearance of (non-existent) duration dependence. Given these difficulties, we develop a solution for self-selectivity bias in duration models and apply this solution to a prominent study of war participation and political leadership tenure. Based on empirical analysis and Monte Carlo simulations, our solution for selectivity bias in duration models is superior to models that ignore the problem.

Underestimating Selection Bias in Political Science: The Unforeseen Consequences of Algorithmic Errors in the Estimation of Heckman Selection Models

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