Robust Instrumental Variables and Accelerated Life Regressions

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  • This thesis considers the econometric problem of endogeneity in an accelerated life regression model. The proposed instrumental variables inference, based on inverting a pivotal statistic, is exact regardless of instrument quality. A (i) least squares statistic and (ii) distribution-free linear rank statistic allowing censoring are provided. A simulation confirms that the quality of exogenous variation determines an instrument’s informative content. We provide an empirical illustration with an original prospectively collected ob- servational data set, in which, the trauma status of a pediatric critical care patient instruments a possibly confounded illness severity index in a length of stay regression for a specific pediatric intensive care population. Results suggest a clinically relevant bias correction for routinely collected patient risk indices that is meaningful for informing policy in the health care setting.

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  • Copyright © 2016 the author(s). Theses may be used for non-commercial research, educational, or related academic purposes only. Such uses include personal study, research, scholarship, and teaching. Theses may only be shared by linking to Carleton University Institutional Repository and no part may be used without proper attribution to the author. No part may be used for commercial purposes directly or indirectly via a for-profit platform; no adaptation or derivative works are permitted without consent from the copyright owner.
Date Created
  • 2016


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