Pemodelan Waktu Survival Pasien Tuberkulosis menggunakan Regresi Cox Proportional Hazard dengan Data Tersensor

Penulis

  • Elsa Oktaviani Universitas Negeri Padang
  • Nonong Amalita
  • Atus Amadi Putra
  • Dony Permana

DOI:

https://doi.org/10.24036/ujsds/vol1-iss4/65

Abstrak

Cox proportional hazard regression is a type of survival analysis that can be applied to tuberculosis cases. This study aims to determine the Cox proportional hazard regression  model and the factors that influence the survival time of tuberculosis patients at RSUP Dr.  M. Djamil Padang. The survival period used is the time when the patient is taking TB treatment at RSUP Dr.  M. Djamil Padang in 2021 until the patient is declared dead. The method used in the Cox Proportional Hazard Regression analysis is the Maximum Partial Likelihood Estimation Method. By using the cox proportional hazard regression model, the factors that influence the survival time of tuberculosis patients at RSUP Dr.  M. Djamil's is BMI (X3) , leukocytes (X5) , fever (X9) , shortness of breath (X11) , and decreased appetite (X12) .  The Cox Proportional Hazard Regression Model obtained is hi(t) = h0(t) exp(1,315X3 + 1,224X5 + 1,138X9 +1,623X11 + 1,251X12).

Unduhan

Diterbitkan

2023-08-28

Cara Mengutip

Elsa Oktaviani, Nonong Amalita, Atus Amadi Putra, & Dony Permana. (2023). Pemodelan Waktu Survival Pasien Tuberkulosis menggunakan Regresi Cox Proportional Hazard dengan Data Tersensor. UNP Journal of Statistics and Data Science, 1(4), 248–255. https://doi.org/10.24036/ujsds/vol1-iss4/65

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