IDEAS home Printed from https://ideas.repec.org/a/taf/japsta/v43y2016i1p72-86.html
   My bibliography  Save this article

Academic performance of students from entrance to graduation via quasi U-statistics: a study at a Brazilian research university

Author

Listed:
  • Rafael Pimentel Maia
  • Hildete Prisco Pinheiro
  • Aluísio Pinheiro

Abstract

We present novel methodology to assess undergraduate students' performance. Emphasis is given to potential dissimilar behaviors due to high school background and gender. The proposed method is based on measures of diversity and on the decomposability of quasi U -statistics to define average distances between and within groups. One advantage of the new method over the classical analysis of variance is its robustness to distributional deviation from the normality. Moreover, compared with other nonparametric methods, it also includes tests for interaction effects which are not rank transform procedures. The variance of the test statistic is estimated by jackknife and p -values are computed using its asymptotic distribution. A college education performance data is analyzed. The data set is formed by students who entered in the University of Campinas, Brazil, between 1997 and 2000. Their academic performance has been recorded until graduation or drop-out. The classical ANOVA points to significant effects of gender, type of high school and working status. However, the residual analysis indicates a highly significant deviation from normality. The quasi U -statistics nonparametric tests proposed here present significant effect of interaction between type of high school and gender but did not present a significant effect of working status. The proposed nonparametric method also results in smaller error variances, illustrating its robustness against model misspecification.

Suggested Citation

  • 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.
    • Handle: RePEc:taf:japsta:v:43:y:2016:i:1:p:72-86
    DOI: 10.1080/02664763.2015.1077939
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/02664763.2015.1077939
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/02664763.2015.1077939?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. Tatiana B. Bordin & Hildete P. Pinheiro & Alu�sio Pinheiro, 2011. "Homogeneity tests among groups for microsatellite data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(9), pages 1951-1962, October.
    2. Renato H. L. Pedrosa & J. Norberto W. Dachs & Rafael P. Maia & Cibele Y. Andrade & Benilton S. Carvalho, 2007. "Academic Performance, Students' Background and Affirmative Action at a Brazilian University," Higher Education Management and Policy, OECD Publishing, vol. 19(3), pages 1-20.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.
    3. Hildete P. Pinheiro & Pranab K. Sen & Aluísio Pinheiro & Samara F. Kiihl, 2020. "A nonparametric approach to assess undergraduate performance," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 74(4), pages 538-558, November.

    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. Hildete P. Pinheiro & Pranab K. Sen & Aluísio Pinheiro & Samara F. Kiihl, 2020. "A nonparametric approach to assess undergraduate performance," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 74(4), pages 538-558, November.

    More about this item

    Statistics

    Access and download statistics

    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:taf:japsta:v:43:y:2016:i:1:p:72-86. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/CJAS20 .

    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.