IDEAS home Printed from https://ideas.repec.org/a/spr/soinre/v146y2019i1d10.1007_s11205-018-1882-7.html
   My bibliography  Save this article

Concomitant-Variable Latent-Class Beta Inflated Models to Assess Students’ Performance: An Italian Case Study

Author

Listed:
  • Marco Centoni

    (Libera Università Maria Ss. Assunta)

  • Vieri Del Panta

    (Libera Università Maria Ss. Assunta)

  • Antonello Maruotti

    (Libera Università Maria Ss. Assunta)

  • Valentina Raponi

    (Sapienza Università di Roma
    Imperial College)

Abstract

Students’ performance is a crucial aspect for university programs effectiveness and organization. In this paper, we introduce and analyze a performance index for the first-year students of a private Italian university, namely the Libera Università Maria Ss. Assunta. We use administrative data on 532 undergraduate students enrolled in any of the eight available bachelor degrees in 2015. Our aim is to improve the general understanding of performance linking it with personal student’s characteristics and with degree-specific aspects. A beta inflated latent class approach is employed to identify clusters of performance establishing a link with all available explanatory variables. The empirical analysis unveils that a good and balanced degree organization may improve students’ performance. The student’s ability plays a crucial role in discriminating between good and bad performances, and also strongly depends on individual-specific characteristics, such as the final mark obtained at high school.

Suggested Citation

  • Marco Centoni & Vieri Del Panta & Antonello Maruotti & Valentina Raponi, 2019. "Concomitant-Variable Latent-Class Beta Inflated Models to Assess Students’ Performance: An Italian Case Study," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 146(1), pages 7-18, November.
  • Handle: RePEc:spr:soinre:v:146:y:2019:i:1:d:10.1007_s11205-018-1882-7
    DOI: 10.1007/s11205-018-1882-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11205-018-1882-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11205-018-1882-7?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jeremy P. Smith & Robin A. Naylor, 2001. "Dropping out of university: A statistical analysis of the probability of withdrawal for UK university students," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 164(2), pages 389-405.
    2. Valentina Raponi & Francesca Martella & Antonello Maruotti, 2016. "A biclustering approach to university performances: an Italian case study," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(1), pages 31-45, January.
    3. Zhaoyi Cao & Tim Maloney, 2017. "Decomposing Ethnic Differences in University Academic Achievement in New Zealand," Working Papers 2017-02, Auckland University of Technology, Department of Economics.
    4. Ospina, Raydonal & Ferrari, Silvia L.P., 2012. "A general class of zero-or-one inflated beta regression models," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1609-1623.
    5. F. Belloc & A. Maruotti & L. Petrella, 2011. "How individual characteristics affect university students drop-out: a semiparametric mixed-effects model for an Italian case study," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(10), pages 2225-2239.
    6. Michela Gnaldi & M. Giovanna Ranalli, 2016. "Measuring University Performance by Means of Composite Indicators: A Robustness Analysis of the Composite Measure Used for the Benchmark of Italian Universities," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 129(2), pages 659-675, November.
    7. Rafael Pimentel Maia & Hildete Prisco Pinheiro & Aluísio Pinheiro, 2016. "Academic performance of students from entrance to graduation via quasi U-statistics: a study at a Brazilian research university," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(1), pages 72-86, January.
    8. Luca Bagnato & Antonio Punzo, 2013. "Finite mixtures of unimodal beta and gamma densities and the $$k$$ -bumps algorithm," Computational Statistics, Springer, vol. 28(4), pages 1571-1597, August.
    9. Peter G. M. van der Heijden & Jos Dessens & UIf Bockenholt, 1996. "Estimating the Concomitant-Variable Latent-Class Model With the EM Algorithm," Journal of Educational and Behavioral Statistics, , vol. 21(3), pages 215-229, September.
    10. Hakim-Moulay Dehbi & Mario Cortina-Borja & Marco Geraci, 2016. "Aranda-Ordaz quantile regression for student performance assessment," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(1), pages 58-71, January.
    11. Marco Enea & Massimo Attanasio, 2016. "An association model for bivariate data with application to the analysis of university students' success," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(1), pages 46-57, January.
    12. Giada Adelfio & Giovanni Boscaino, 2016. "Degree course change and student performance: a mixed-effect model approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(1), pages 3-15, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Contini, Dalit & Salza, Guido, 2020. "Too few university graduates. Inclusiveness and effectiveness of the Italian higher education system," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    2. Hildete P. Pinheiro & Rafael P. Maia & Eufrásio A. Lima Neto & Mariana Rodrigues-Motta, 2019. "Zero-one augmented beta and zero-inflated discrete models with heterogeneous dispersion for the analysis of student academic performance," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(4), pages 749-767, December.
    3. Cristine Rauber & Francisco Cribari-Neto & Fábio M. Bayer, 2020. "Improved testing inferences for beta regressions with parametric mean link function," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(4), pages 687-717, December.
    4. Paola Perchinunno & Massimo Bilancia & Domenico Vitale, 2021. "A Statistical Analysis of Factors Affecting Higher Education Dropouts," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 156(2), pages 341-362, August.
    5. Diego Ramos Canterle & Fábio Mariano Bayer, 2019. "Variable dispersion beta regressions with parametric link functions," Statistical Papers, Springer, vol. 60(5), pages 1541-1567, October.
    6. Enrico Bergamini & Georg Zachmann, 2020. "Exploring EU’s Regional Potential in Low-Carbon Technologies," Sustainability, MDPI, vol. 13(1), pages 1-28, December.
    7. Gourieroux, Christian & Lu, Yang, 2019. "Least impulse response estimator for stress test exercises," Journal of Banking & Finance, Elsevier, vol. 103(C), pages 62-77.
    8. Guillermo Martínez-Flórez & Artur J. Lemonte & Germán Moreno-Arenas & Roger Tovar-Falón, 2022. "The Bivariate Unit-Sinh-Normal Distribution and Its Related Regression Model," Mathematics, MDPI, vol. 10(17), pages 1-26, August.
    9. Salvatore D. Tomarchio & Antonio Punzo, 2019. "Modelling the loss given default distribution via a family of zero‐and‐one inflated mixture models," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 182(4), pages 1247-1266, October.
    10. Michela Gnaldi & Simone Del Sarto, 2018. "Variable Weighting via Multidimensional IRT Models in Composite Indicators Construction," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 136(3), pages 1139-1156, April.
    11. Rita Takács & Szabolcs Takács & Judit T. Kárász & Attila Oláh & Zoltán Horváth, 2023. "The impact of the first wave of COVID-19 on students’ attainment, analysed by IRT modelling method," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-10, December.
    12. Aina, Carmen & Baici, Eliana & Casalone, Giorgia & Pastore, Francesco, 2018. "The Economics of University Dropouts and Delayed Graduation: A Survey," IZA Discussion Papers 11421, Institute of Labor Economics (IZA).
    13. Vignoles Anna F & Powdthavee Nattavudh, 2009. "The Socioeconomic Gap in University Dropouts," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 9(1), pages 1-36, April.
    14. Carlos Rojas & Bernardo Riffo & Ernesto Guerra, 2023. "Word Retrieval After the 80s: Evidence From Specific and Multiple Words Naming Tasks," SAGE Open, , vol. 13(2), pages 21582440231, May.
    15. Salvatore Ingrassia & Antonio Punzo & Giorgio Vittadini & Simona Minotti, 2015. "Erratum to: The Generalized Linear Mixed Cluster-Weighted Model," Journal of Classification, Springer;The Classification Society, vol. 32(2), pages 327-355, July.
    16. Contini, Dalit & Salza, Guido & Scagni, Andrea, 2017. "Dropout and Time to Degree in Italian Universities Around the Economic Crisis," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201716, University of Turin.
    17. Reboul, E. & Guérin, I. & Nordman, C.J., 2021. "The gender of debt and credit: Insights from rural Tamil Nadu," World Development, Elsevier, vol. 142(C).
    18. Jobst, Rainer & Kellner, Ralf & Rösch, Daniel, 2020. "Bayesian loss given default estimation for European sovereign bonds," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1073-1091.
    19. Zhang, Ganggang & Wu, Jie & Zhu, Qingyuan, 2020. "Performance evaluation and enrollment quota allocation for higher education institutions in China," Evaluation and Program Planning, Elsevier, vol. 81(C).
    20. Maria Marchenko, 2019. "Endogenous Shocks in Social Networks: Exam Failures and Friends' Future Performance," Department of Economics Working Papers wuwp292, Vienna University of Economics and Business, Department of Economics.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:soinre:v:146:y:2019:i:1:d:10.1007_s11205-018-1882-7. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.