Henao Ceballos, Ferney

Profile Picture

Filters

20231
Reset filters

Settings

Citations

Publication Search Results

Now showing 1 - 1 of 1
  • Thumbnail Image
    Publication
    Censored zero-inflated Poisson regression models: Predicting success in undergraduate math courses
    (2023-03-29) Henao Ceballos, Ferney; Macchiavelli, Raúl E.; College of Arts and Sciences - Sciences; Cáceres Duque, Luis F.; Lorenzo González, Edgardo; Rolke, Wolfgang A.; Department of Mathematics; Ferrer Alameda, Mercedes
    Regression models explain the relation between a dependent variable (response variable) and a set of independent variables (predictor variables). In some cases, there are values of the dependent variable that cannot be observed. For example, consider the number of times a student repeats a class until passing it. Any study of this type will have a time limit, after which we will have to perform the data analysis. It is expected that at the time of data collection, there are still students who have not passed the class, and therefore we do not know the number of times these students would repeat it until passing, but we do know that this amount is greater than the observed value. In this case, we will say that the observation is censored. On other hand, a high percentage of students pass the class without repeating it, that is, there is a large percentage of zeros. In these cases, we will have censored zero-inflated count data. We propose new likelihood equations for this regression model using the Poisson distribution and study its statistical properties using simulations. Finally, we apply the model to a data set of students from the University of Puerto Rico to find models that predict if a student is at risk of failing introductory undergraduate math classes and how many times (on average) he or she may need to repeat the class.