Binary Logistic Regression Model of Stroke Patients: A Case Study of Stroke Centre Hospital in Makassar

Annas, Suwardi and Aswi, Aswi and Abdy, Muhammad and Poerwanto, Bobby (2022) Binary Logistic Regression Model of Stroke Patients: A Case Study of Stroke Centre Hospital in Makassar. Indonesian Journal of Statistics and Its Applications, 6 (1). pp. 161-169. ISSN 2599-0802

	Text 3. Jurnal Sinta 3_PenulisPertma_koresponden_Fix.pdf - Published Version Download (191kB)
	Text 3. Hasil Turnitin Jurnal Sinta 3_PenulisPertma_koresponden_Fix.pdf - Additional Metadata Download (1MB)
	Text 3. Hasil Review Jurnal Sinta 3_PenulisPertma_koresponden_Fix.pdf - Additional Metadata Download (1MB)
	Text 3. Jejak Korespondensi Jurnal Sinta 3_PenulisPertma_koresponden_Fix.pdf - Additional Metadata Download (281kB)

Abstract

This paper aimed to determine factors that affect significantly types of stroke for stroke patients in Dadi Stroke Center Hospital. The binary logistic regression model was used to analyze the association between the types of stroke and some covariates namely age, sex, total cholesterol, blood sugar level, and history of diseases (hypertension/stroke/diabetes mellitus). Maximum Likelihood Estimation was used to estimate parameters. Combinations of covariates were compared using goodness-of-fit measures. Comparisons were made in the context of a case study, namely stroke patients (2017-2020). The results showed that a binary logistic model combining the history of diseases and blood sugar level provided the most suitable model as it has the smallest AIC and covariates included are statistically significant. The coefficient estimation of the history of diseases variable is -0.92402 with an odds ratio value exp (-0.92402)=0.4. This means that stroke patients who have a history of diseases experience a reduction of 60% in the odds of having a hemorrhagic stroke compared to stroke patients that do not have a history of diseases. In other words, stroke patients who have a history of diseases tend to have a non-hemorrhagic stroke. Furthermore, the coefficient estimation of blood sugar level is 0.74395 with an odds ratio value exp(0.74395)=2. It means that stroke patients who do not have normal blood sugar levels tend to have a hemorrhagic stroke 2 times greater than stroke patients with normal blood sugar levels. A history of diseases and blood sugar level were factors that significantly affect the types of stroke.

Item Type:	Article
Subjects:	FMIPA > STATISTIKA - (S1) FMIPA > Matematika
Divisions:	FAKULTAS MIPA
Depositing User:	FMIPA UNM
Date Deposited:	30 Aug 2022 05:43
Last Modified:	30 Aug 2022 05:43
URI:	http://eprints.unm.ac.id/id/eprint/24471

Actions (login required)

View Item