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The evaluation of university educational processes: a quantile regression approach

Author

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  • Cristina Davino
  • Domenico Vistocco

Abstract

The paper aims to analyse the internal effectiveness of an niversity educational process by means of quantile regression. In particular, the goal is to evaluate how the students features affect the utcome of the University careers taking into account that this effect can be different for students with good or bad performances.

Suggested Citation

  • Cristina Davino & Domenico Vistocco, 2007. "The evaluation of university educational processes: a quantile regression approach," Statistica, Department of Statistics, University of Bologna, vol. 67(3), pages 281-292.
    • Handle: RePEc:bot:rivsta:v:67:y:2007:i:3:p:281-292
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    Cited by:

    1. Cristina Davino & Vincenzo Esposito Vinzi, 2016. "Quantile composite-based path modeling," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 10(4), pages 491-520, December.
    2. C. Davino & R. Romano & D. Vistocco, 2022. "Handling multicollinearity in quantile regression through the use of principal component regression," METRON, Springer;Sapienza Università di Roma, vol. 80(2), pages 153-174, August.

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