The Zero-Inflated Negative Binomial Semiparametric Regression Model: Application to Number of Failing Grades Data

Elton G. Aráujo (), Julio C. S. Vasconcelos (), Denize P. Santos (), Edwin M. M. Ortega (), Dalton Souza () and João P. F. Zanetoni ()
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Elton G. Aráujo: Universidade Federal de Mato Grosso do Sul
Julio C. S. Vasconcelos: Universidade de São Paulo
Denize P. Santos: Universidade de São Paulo
Edwin M. M. Ortega: Universidade de São Paulo
Dalton Souza: Universidade Federal de Mato Grosso do Sul
João P. F. Zanetoni: Universidade Federal de Mato Grosso do Sul

Annals of Data Science, 2023, vol. 10, issue 4, No 6, 1006 pages

Abstract: Abstract In this paper we study the performance of college students, measured by the number of failing grades, considering various covariables that can positively or negatively influence this performance. The students in the sample were undergraduate business majors studying at night at a federal public university in the state of Mato Grosso do Sul, Brazil. Among the factors considered are covariables that had a linear and nonlinear relationship with the students’ performance. We also observed a high percentage of zeros, the reason we used a zero-inflated semiparametric regression model based on the negative binomial distribution to analyze our dataset.We used the penalized maximum likelihood method along with analysis of the residuals to verify the model’s assumptions. We present results, discussion and conclusions about the number of subjects failed by the students.

Keywords: Cubic smoothing splines; Education data; Negative binomial distribution; Zero-inflated models (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s40745-021-00350-z

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