- ASA 2021 Statistics and Information Systems for Policy Evaluation
- Edited by Bruno Bertaccini, Luigi Fabbris, Alessandra Petrucci
Nonparametric methods for stratified C-sample designs: a case study
- Rosa Arboretti
- Riccardo Ceccato
- Luigi Salmaso
- © 2021 Author(s) |
- CC BY 4.0
- DOI: 10.36253/978-88-5518-304-8.05
Several parametric and nonparametric methods have been proposed to deal with stratified C-sample problems where the main interest lies in evaluating the presence of a certain treatment effect, but the strata effects cannot be overlooked. Stratified scenarios can be found in several different fields. In this paper we focus on a particular case study from the field of education, addressing a typical stochastic ordering problem in the presence of stratification. We are interested in assessing how the performance of students from different degree programs at the University of Padova change, in terms of university credits and grades, when compared with their entry test results. To address this problem, we propose an extension of the Non-Parametric Combination (NPC) methodology, a permutation-based technique (see Pesarin and Salmaso, 2010), as a valuable tool to improve the data analytics for monitoring University students’ careers at the School of Engineering of the University of Padova. This new procedure indeed allows us to assess the efficacy of the University of Padova’s entry tests in evaluating and selecting future students.
- Keywords:
- Nonparametric permutation,
- Evaluation of Educational Systems,
University of Padua, Italy - ORCID: 0000-0003-1263-0440
University of Padua, Italy - ORCID: 0000-0002-8629-8439
University of Padua, Italy - ORCID: 0000-0001-6501-1585
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Chapter Information
Chapter Title
Nonparametric methods for stratified C-sample designs: a case study
Authors
Rosa Arboretti, Riccardo Ceccato, Luigi Salmaso
Language
English
DOI
10.36253/978-88-5518-304-8.05
Peer Reviewed
Publication Year
2021
Copyright Information
© 2021 Author(s)
Content License
Metadata License
Bibliographic Information
Book Title
ASA 2021 Statistics and Information Systems for Policy Evaluation
Book Subtitle
Book of short papers of the opening conference
Editors
Bruno Bertaccini, Luigi Fabbris, Alessandra Petrucci
Peer Reviewed
Publication Year
2021
Copyright Information
© 2021 Author(s)
Content License
Metadata License
Publisher Name
Firenze University Press
DOI
10.36253/978-88-5518-304-8
eISBN (pdf)
978-88-5518-304-8
eISBN (xml)
978-88-5518-305-5
Series Title
Proceedings e report
Series ISSN
2704-601X
Series E-ISSN
2704-5846