Vallejos, Catalina and Steel, Mark F. J. (2014): Bayesian Survival Modelling of University Outcomes.
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Abstract
The aim of this paper is to model the length of registration at university and its associated academic outcome for undergraduate students at the Pontificia Universidad Cat´olica de Chile. Survival time is defined as the time until the end of the enrollment period, which can relate to different reasons - graduation or two types of dropout - that are driven by different processes. Hence, a competing risks model is employed for the analysis. The issue of separation of the outcomes (which precludes maximum likelihood estimation) is handled through the use of Bayesian inference with an appropriately chosen prior. We are interested in identifying important determinants of university outcomes and the associated model uncertainty is formally addressed through Bayesian model averaging. The methodology introduced for modelling university outcomes is applied to three selected degree programmes, which are particularly affected by dropout and late graduation.
Item Type: | MPRA Paper |
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Original Title: | Bayesian Survival Modelling of University Outcomes |
Language: | English |
Keywords: | Bayesian model averaging; Competing risks; Outcomes separation; Proportional Odds model; University dropout |
Subjects: | C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C11 - Bayesian Analysis: General C - Mathematical and Quantitative Methods > C4 - Econometric and Statistical Methods: Special Topics > C41 - Duration Analysis ; Optimal Timing Strategies I - Health, Education, and Welfare > I2 - Education and Research Institutions > I23 - Higher Education ; Research Institutions |
Item ID: | 57185 |
Depositing User: | Mark F.J. Steel |
Date Deposited: | 09 Jul 2014 21:11 |
Last Modified: | 27 Sep 2019 08:19 |
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URI: | https://mpra.ub.uni-muenchen.de/id/eprint/57185 |