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Huge number of Sudanese children, under age of five, were affected mostly by 10 types of diseases, among which 5 were very widely spread (acute renal failure, congenital deformity of heart, leukemia, septicemia and sickle cell disease). These diseases increased children death rate. The AFT model was an alternative method for the analysis of survival data even when hazards were not proportional. Based on asymptotic results, the AFT models should lead to more efficient parameter estimates than Cox model under certain circumferences. Cox PH model is the most commonly used method, but survival…mehr

Produktbeschreibung
Huge number of Sudanese children, under age of five, were affected mostly by 10 types of diseases, among which 5 were very widely spread (acute renal failure, congenital deformity of heart, leukemia, septicemia and sickle cell disease). These diseases increased children death rate. The AFT model was an alternative method for the analysis of survival data even when hazards were not proportional. Based on asymptotic results, the AFT models should lead to more efficient parameter estimates than Cox model under certain circumferences. Cox PH model is the most commonly used method, but survival analysis, after examining the covariate effects on the hazard function, proposed (AFT) model, unfortunately this method is rarely used. The objective of the analysis was to determine whether the diseases preventive therapies affected children, under age of five, mortality and survival. It was concluded AFT model can be an alternative to the PH model in the analysis and evaluation of the effectsof the large censoring data. Analysis suggested PH model may not be appropriate in some situations, and the AFT model could provide a more appropriate description of the dataset.
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Autorenporträt
Khalid Mustafa Shoaib, Master degree in Statistics: Mathematical and Computer Sciences at University of Gezira - Sudan, Project Support Officer at United Nations Development Programme, Sudan.