Using Logistic Regression and Cox Regression Models to Studying the Most Prognostic Factors for Leukemia patients
DOI:
https://doi.org/10.25212/lfu.qzj.4.3.20Keywords:
Survival Analysis, logistic regression, Cox regression model, Hazard Function, Leukemia..Abstract
The basic idea of this study focused on the using of two advanced statistical methods for studding the most important factors affecting the leukemia in Erbil city. The logistic regression was chosen and Cox regression as being applicable on this studies. The results indicated that, in spite of the different regression coefficients in somewhat to logistic regression and Cox regression, have not reached to the same variables that have an impact on the phenomenon. Moreover the results indicated that the surgery is the most important factor affecting the leukemia survival patients in both methods. validation was done by calculating two model selecting criterion; Akaike Information Criterion (AIC) and Bayesian information criterion (BIC) of each models are compared the smaller values of them. The data set of this study was obtained from Nanakali Hospital in the period from 1st January 2013 to 31st December 2018. The results obtained by utilizing the statistical packages ( Mat-lab and SPSS).
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