IDEAS home Printed from https://ideas.repec.org/a/spr/qualqt/v51y2017i6d10.1007_s11135-016-0408-0.html
   My bibliography  Save this article

Goodness of fit measures for logistic regression model: an application for students’ evaluations of university teaching

Author

Listed:
  • Biagio Simonetti

    (University of Sannio)

  • Pasquale Sarnacchiaro

    (University Unitelma-La Sapienza di Roma)

  • M. Rosario González Rodríguez

    (University of Seville)

Abstract

This study investigates the assessment of university teachers. The evaluation of university teaching plays an important role in the university system in the light of the fact, that a part of the financial transfer from educational ministry is based on the quality of teaching. From Statistical point of view the use of regression models has been widely applied in this area. The logistic regression model is particularly used as discrete choice model using dichotomous dependent variable. For many regression analyses the lack of a goodness-of-fit measure is more important than coefficient interpretability. The goal of this paper is to present an overview of a few easily employed methods for assessing the model fitness of Logistic Regression Model by Pseudo- $$R^{2}$$ R 2 .Moreover the assessment is carried out through a simulation study to analyse the pattern (behaviour) of each measure, with precise focus on change of multiple correlation among the variables. In this paper a survey on student satisfaction (SS) of university teaching system was conducted. The instrument used in this paper is a questionnaire proposed by a different research group in 2010. The collected data was elaborated by a full reflective Structural Equation Model using PLS path model estimation. The initial results showed that the influence of the Organization and Infrastructures on the Student Satisfaction were statistically insignificant. Therefore a more complex model was supposed, the final results showed that the influence of Organization and Infrastructures on the SS was indirect, that is the Organization and the Infrastructures exert an influence upon the SS through the Didactics.

Suggested Citation

  • Biagio Simonetti & Pasquale Sarnacchiaro & M. Rosario González Rodríguez, 2017. "Goodness of fit measures for logistic regression model: an application for students’ evaluations of university teaching," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(6), pages 2545-2554, November.
    • Handle: RePEc:spr:qualqt:v:51:y:2017:i:6:d:10.1007_s11135-016-0408-0
    DOI: 10.1007/s11135-016-0408-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11135-016-0408-0
    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/s11135-016-0408-0?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. Amemiya, Takeshi, 1981. "Qualitative Response Models: A Survey," Journal of Economic Literature, American Economic Association, vol. 19(4), pages 1483-1536, December.
    2. Veall, Michael R & Zimmermann, Klaus F, 1996. "Pseudo-R-[superscript 2] Measures for Some Common Limited Dependent Variable Models," Journal of Economic Surveys, Wiley Blackwell, vol. 10(3), pages 241-259, September.
    3. Dhrymes, Phoebus J., 1986. "Limited dependent variables," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 3, chapter 27, pages 1567-1631, Elsevier.
    4. John G. Cragg & Russell S. Uhler, 1970. "The Demand for Automobiles," Canadian Journal of Economics, Canadian Economics Association, vol. 3(3), pages 386-406, August.
    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. Francesca Fortuna & Fabrizio Maturo, 2019. "K-means clustering of item characteristic curves and item information curves via functional principal component analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(5), pages 2291-2304, September.
    2. Sharon Tan & Evan Lau & Hiram Ting & Jun-Hwa Cheah & Biagio Simonetti & Tan Hiok Lip, 2019. "How Do Students Evaluate Instructors’ Performance? Implication of Teaching Abilities, Physical Attractiveness and Psychological Factors," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 146(1), pages 61-76, November.
    3. Yu Hao & Shuang Liu & Zhu Liduzi Jiesisibieke & Yi-Jie Xu, 2019. "What Determines University Students’ Online Consumer Credit? Evidence From China," SAGE Open, , vol. 9(1), pages 21582440198, March.

    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. Estrella, Arturo, 1998. "A New Measure of Fit for Equations with Dichotomous Dependent Variables," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 198-205, April.
    2. Michael Veall & Klaus Zimmermann, 1994. "Evaluating Pseudo-R 2 's for binary probit models," Quality & Quantity: International Journal of Methodology, Springer, vol. 28(2), pages 151-164, May.
    3. Seifert-Vogt, Hans G., 1988. "Die ökonometrische Spezifikation eines sequentiellen Modells der Rückkehrentscheidungen ausländischer Arbeiter aus dem Gastland in ihr Heimatland," Discussion Papers, Series II 57, University of Konstanz, Collaborative Research Centre (SFB) 178 "Internationalization of the Economy".
    4. Gerdtham, Ulf-G. & Johannesson, Magnus, 1999. "New estimates of the demand for health: results based on a categorical health measure and Swedish micro data," Social Science & Medicine, Elsevier, vol. 49(10), pages 1325-1332, November.
    5. Selen CAKMAKYAPAN & Atilla GOKTAS, 2013. "A Comparison Of Binary Logit And Probit Models With A Simulation Study," Journal of Social and Economic Statistics, Bucharest University of Economic Studies, vol. 2(1), pages 1-17, JULY.
    6. Xinyu Zhang & Alan T. K. Wan & Sherry Z. Zhou, 2011. "Focused Information Criteria, Model Selection, and Model Averaging in a Tobit Model With a Nonzero Threshold," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 132-142, June.
    7. Ralph Rotte & Christoph Schmidt, 2003. "On the production of victory: Empirical determinants of battlefield success in modern war," Defence and Peace Economics, Taylor & Francis Journals, vol. 14(3), pages 175-192.
    8. Selen Cakmakyapan & Haydar Demirhan, 2017. "A Monte Carlo-based pseudo-coefficient of determination for generalized linear models with binary outcome," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(14), pages 2458-2482, October.
    9. PASCUAL, Roberto & VEREDAS, David, 2004. "What pieces of limit order book information are informative ?," LIDAM Discussion Papers CORE 2004033, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    10. Roberto Pascual & David Veredas, 2009. "What pieces of limit order book information matter in explaining order choice by patient and impatient traders?," Quantitative Finance, Taylor & Francis Journals, vol. 9(5), pages 527-545.
    11. MARK McGILLIVRAY & EDWARD OCZKOWSKI, 1991. "Modelling the Allocation of Australian Bilaterial Aid: A Two‐Part Sample Selection Approach," The Economic Record, The Economic Society of Australia, vol. 67(2), pages 147-152, June.
    12. Ahn T. Le, 2003. "Female Labour Market Participation: Differences Between Primary and Tied Movers," Economics Discussion / Working Papers 03-17, The University of Western Australia, Department of Economics.
    13. Lovejoy, Kristin, 2012. "Mobility Fulfillment Among Low-car Households: Implications for Reducing Auto Dependence in the United States," Institute of Transportation Studies, Working Paper Series qt4v44b5qn, Institute of Transportation Studies, UC Davis.
    14. Arturo Estrella & Anthony P. Rodrigues, 1998. "Consistent covariance matrix estimation in probit models with autocorrelated errors," Staff Reports 39, Federal Reserve Bank of New York.
    15. T.R.L. Fry & R.D. Brooks & Br. Comley & J. Zhang, 1993. "Economic Motivations for Limited Dependent and Qualitative Variable Models," The Economic Record, The Economic Society of Australia, vol. 69(2), pages 193-205, June.
    16. Paleti, Rajesh, 2018. "Generalized multinomial probit Model: Accommodating constrained random parameters," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 248-262.
    17. Maria Iacovou, 2002. "Class Size in the Early Years: Is Smaller Really Better?," Education Economics, Taylor & Francis Journals, vol. 10(3), pages 261-290.
    18. Erik Stam & Roy Thurik & Peter van der Zwan, 2010. "Entrepreneurial exit in real and imagined markets," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 19(4), pages 1109-1139, August.
    19. Patrick A. Puhani, 2000. "On the Identification of Relative Wage Rigidity Dynamics," William Davidson Institute Working Papers Series 343, William Davidson Institute at the University of Michigan.
    20. Haoying Wang & Guohui Wu, 2022. "Modeling discrete choices with large fine-scale spatial data: opportunities and challenges," Journal of Geographical Systems, Springer, vol. 24(3), pages 325-351, July.

    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:qualqt:v:51:y:2017:i:6:d:10.1007_s11135-016-0408-0. 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.