Survival Time in Higher Education Program after a Dropout Using Modified Survival Function: A Retrospective Study to Predict Average Graduation Time and Factors Leading to Early Dropout

The case recurrence survival model in terms of case retention after at least one dropout is still difficult to investigate, and some concrete framework is required to derive the survival model in order to achieve more precise results and reduce the magnitude of bias that may occur during dropout, reappearance, and retention either until the last or dropout again. The data for this retrospective, longitudinal study was retrieved based on undergraduate program students spanning eight years. All relevant information was entered into the data worksheet of SPSS-29.0 (IBM product, USA). Syntax programming of survival algorithm was developed using the statistical programming software R version-4.2.1, and survival parameters were generated. The survival probability of the existing model compared to the modified function showed minimal differences. The survival rate was 94% in the first year of study, with a gradual decline of 1% - 3% annually, reaching 91.6% by the end of the fifth year. The average survival time for the existing survival function was 4.666 ± 3.25 years, whereas the modified function exhibited a higher average of 5.584 ± 3.61 years. Similarly, the mean graduation time was slightly higher for the modified function (6.10 ± 0.302 years) compared to the existing model (6 ± 0.0 years). Model performance, assessed using the R² value revealed the modified survival model than existing model was more accurate and preferable (i.e. 0.903 vs. 0.808). It was concluded that dropout cases, which were censored in the existing survival model, played a significant role in estimating students’ survival time and the program’s graduation time. Hence, the modified function can be preferred when the first event to time doesn’t represent the final outcome.