Browsing by Author "Alarcón Bustamante, Eduardo Sebastián"

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    From missing data to informative GPA predictions: Navigating selection process beliefs with the partial identifiability approach
    (John Wiley and Sons Ltd, 2024) Alarcón Bustamante, Eduardo Sebastián; González Burgos, Jorge Andrés; Torres Irribarra, David Esteban; San Martin Gutiérrez, Ernesto Javier
    The extent to which college admissions test scores can forecast college grade point average (GPA) is often evaluated in predictive validity studies using regression analyses. A problem in college admissions processes is that we observe test scores for all the applicants; however, we cannot observe the GPA of applicants who were not selected. The standard solution to tackle this problem has relied upon strong assumptions to identify the exact value of the regression function in the presence of missing data. In this paper, we present an alternative approach based on the theory of partial identifiability that considers a variety of milder assumptions to learn about the regression function. Using a university admissions dataset we illustrate how results can vary as a function of the assumptions that one is willing to make about the selection process.
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    Modelling predictive validity problems : a partial identification approach
    (2021) Alarcón Bustamante, Eduardo Sebastián; San Martín, Ernesto; Pontificia Universidad Católica de Chile. Facultad de Matemáticas
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    Predictive validity under partial observability
    (Springer, 2020) Alarcón Bustamante, Eduardo Sebastián; San Martín, Ernesto; González Burgos, Jorge Andrés
    To assess the predictive capacity of selection tests is a challenge because the response variable is observed only in selected individuals. In this paper we propose to evaluate the predictive capacity of selection tests through marginal effects under a partial identification approach. Identification bounds are defined for the marginal effects under monotonicity assumptions of the response variable. Theperformance of our method is assessed using a real data set from the university selection test applied in Chile and compared with the marginal effect of the traditional model used in Chile to evaluate the predictive capacity of the selection test.