ANALISIS LAJU PERBAIKAN KONDISI KLINIS PASIEN STROKE MENGGUNAKAN REGRESI HAZARD ADITIF LIN-YING (Studi Kasus: Data Pasien Stroke di RSUD Pandan Arang Boyolali Periode Januari 2021 - Agustus 2021) - Alfiya Nurwidi Hastuti; Yuciana Wilandari; Sudarno Sudarno (Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro, 2022)
Additive hazard regression is a survival analysis that is an alternative to Cox proportional hazard regression. The additive hazard models that have been developed include the Aalen additive hazard model and the Lin-Ying. In this study, Lin-Ying additive hazard regression was used as an analytical method to be applied in stroke data that had been hospitalized at Pandan Arang Hospital Boyolali. This method is considered more effective because there is no assumption of proportionality. The purpose of using this method in this study are analyze the characteristics of stroke patients, form a Lin-Ying additive hazard regression model, find out the factors that affect the rate of improvement of the clinical condition of stroke patients, and interpret the model. Based on the analysis that has been done, the average length of hospitalization is 4,471 days ≈ 4 days, and the factors that significantly affect the rate of improvement of clinical conditions in stroke patients at Pandan Arang Hospital Boyolali are blood pressure and blood sugar.