MODELING FACTORS CAUSING ALZHEIMER’S DISEASE USING LOGIT, PROBIT, AND GOMPIT LINK FUNCTIONS IN GENERALIZED LINEAR MODEL

  • Ardi Kurniawan Department of Mathematics, Faculty of Science and Technology, Universitas Airlangga, Indonesia https://orcid.org/0000-0002-2840-2154
  • Gabriella Agnes Budijono Department of Mathematics, Faculty of Science and Technology, Universitas Airlangga, Indonesia https://orcid.org/0009-0006-7870-2637
  • Kimberly Maserati Siagian Department of Mathematics, Faculty of Science and Technology, Universitas Airlangga, Indonesia https://orcid.org/0009-0003-7271-3149
  • Adrian Wahyu Abdillah Department of Mathematics, Faculty of Science and Technology, Universitas Airlangga, Indonesia https://orcid.org/0009-0008-4471-8379
DOI: https://doi.org/10.30598/barekengvol19iss4pp2877-2890
Keywords: Alzheimer, Generalized Linear Model, Gompit, Gompit Link Functions Logit

Abstract

This study addresses the ongoing challenge of clarifying the risk factors contributing to Alzheimer's disease, a neurodegenerative condition marked by progressive cognitive decline and memory dysfunction, with cases rising globally. To provide a more accurate and comprehensive understanding of the predictors associated with the disease, this research models the contributing factors using logit, probit, and gompit link functions within the Generalized Linear Model (GLM). Utilizing secondary data from 2024, which includes predictor variables such as age, family history, head injury, hypertension, memory complaints, and behavioral disturbances, this research models the relationship between these variables and Alzheimer's diagnosis. The analysis finds that the logit, probit, and gompit link functions yield significant results in identifying risk factors associated with Alzheimer's diagnosis, particularly memory complaints and behavioral disturbances. The gompit link is selected as the best model due to its highest deviance R-squared value of 30.01%, indicating better reliability in predicting Alzheimer's diagnosis than other models. This GLM approach provides insights to support early prevention and intervention efforts for Alzheimer's disease and contribute to achieving Sustainable Development Goals (SDGs) number 3 on good health and well-being.

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Published
2025-09-01
How to Cite
[1]
A. Kurniawan, G. A. Budijono, K. M. Siagian, and A. W. Abdillah, “MODELING FACTORS CAUSING ALZHEIMER’S DISEASE USING LOGIT, PROBIT, AND GOMPIT LINK FUNCTIONS IN GENERALIZED LINEAR MODEL”, BAREKENG: J. Math. & App., vol. 19, no. 4, pp. 2877-2890, Sep. 2025.
Issue
Vol 19 No 4 (2025): BAREKENG: Journal of Mathematics and Its Application
Section
Articles

Copyright (c) 2025 Ardi Kurniawan, Gabriella Agnes Budijono, Kimberly Maserati Siagian, Adrian Wahyu Abdillah

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