Modelling two types of heterogeneity in the analysis of student success

DOI10.1080/02664763.2019.1601164OpenAlexW2931131181MaRDI QIDQ5036928

Juliana Cobre, Sandra Cristina de Oliveira, Fabiana Arca Cruz Tortorelli

Publication date: 25 February 2022

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2019.1601164

zbMATH Keywords

heterogeneitymixture modellong durationdropout ratestudent success

Mathematics Subject Classification ID

Applications of statistics (62Pxx)

Uses Software

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Cites Work

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• Identifiability of cure models revisited
• A classification tree approach for the modeling of competing risks in discrete time
• A new condition for identifiability of finite mixture distributions
• Statistical predictor identification
• A Generalization of the Gamma Distribution
• Identifiability of cure models

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