Volume 13, Issue 7 (July 2026), Pages: 222-230

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 Original Research Paper

Modeling student retention in higher education: A time-to-event survival analysis of key determinants

 Author(s): 

Joseph B. Campit *

 Affiliation(s):

Science and Mathematics Department, College of Teacher Education, Pangasinan State University, Pangasinan, Philippines

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 * Corresponding Author. 

   Corresponding author's ORCID profile:  https://orcid.org/0009-0007-3538-3637

 Digital Object Identifier (DOI)

 
https://doi.org/10.21833/ijaas.2026.07.021

 Abstract

Student retention is a critical indicator of both student success and institutional effectiveness in higher education. This study examines student retention in Philippine higher education institutions (HEIs) using a time-to-event modeling approach through survival analysis, providing a longitudinal perspective on student persistence. Institutional records from 961 undergraduate students at Pangasinan State University, Bayambang Campus, covering School Years 2019–2020 to 2022–2023, were analyzed. The dataset included semester-level enrollment and dropout data, along with demographic and academic characteristics such as sex, course, and class schedule. Retention patterns were assessed using life table analysis, Kaplan–Meier (KM) estimation, Log-Rank tests, and discrete-time survival modeling via generalized estimating equations (GEE). The results indicate that the first semester has the highest observed dropout rate and that survival probabilities decline in subsequent semesters. Observed differences were found across sex, academic program, and class schedule: female students, students in the Bachelor of Science in Business Administration (BSBA), and day-class students showed longer persistence. Discrete-time modeling confirmed these patterns, indicating higher odds of dropout among male students, students in certain programs, and evening-class students. By applying established time-to-event analysis methods to semester-level institutional data, this study provides context-specific evidence on observed retention patterns and the timing of student dropout. These findings offer practical insights for administrators and policymakers to design data-driven retention strategies and targeted support programs, particularly in developing-country higher education contexts.

 © 2026 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords

Student retention, Survival analysis, Higher education, Student dropout, Persistence

 Article history

Received 9 April 2026, Received in revised form 22 July 2026, Accepted 30 July 2026

 Acknowledgment

No Acknowledgment. 

 Compliance with ethical standards

 Ethical considerations

Ethical approval was obtained from the University Research Ethics Board of Pangasinan State University under Protocol No. 2024-0012a-CAMPIT-MODELING, dated March 18, 2024. Permission to access the institutional data was obtained from the appropriate authorities. All data were treated confidentially, and no personal identifiers were included in the dataset. The data were used solely for academic and research purposes. 

 Citation:

Campit JB (2026). Modeling student retention in higher education: A time-to-event survival analysis of key determinants. International Journal of Advanced and Applied Sciences, 13(7): 222-230

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