AN EXPECTATION-CONDITIONAL MAXIMIZATION-BASED WEIBULL-GOMPERTZ MIXTURE MODEL FOR ANALYZING COMPETING-RISKS DATA: USING POST-TRANSPLANT MALIGNANCY DATA

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SALESI MAHMOOD; RAHIMI FOROUSHANI ABBAS; MOHAMMADI JAMILE; ROSTAMI ZOHREH; MEHRAZMAY ALI REZA; EINOLLAHI BEHZAD; KARAMBAKSH ALI REZA; ASGHARIAN SAEED; ESHRAGHIAN MOHAMMAD REZA

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Journal: Journal of Biostatistics and Epidemiology Year:2016 | Volume:2 | Issue:1 Page(s): 1-8

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Title

AN EXPECTATION-CONDITIONAL MAXIMIZATION-BASED WEIBULL-GOMPERTZ MIXTURE MODEL FOR ANALYZING COMPETING-RISKS DATA: USING POST-TRANSPLANT MALIGNANCY DATA

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Keywords

MIXTURE MODELS

COMPETING RISKS

EXPECTATION-CONDITIONAL MAXIMIZATION ALGORITHM

POST-TRANSPLANT MALIGNANCY

Abstract

The aim of this study is to introduce a parametric mixture model to analysis the competing-risks data with two types of failure. In mixture context, ith type of failure is i th component. The baseline failure time for the first and second types of failure are modeled as proportional hazard models according to Weibull and Gompertz distributions, respectively. The covariates affect on both the probability of occurrence and the hazards of the failure types. The probability of occurrence is modeled to depend on covariates through the logistic model. The parameters can be estimated by application of the expectation-conditional maximization and Newton-Raphson algorithms. The simulation studies are performed to compare the proposed model with parametric cause-specific and Fine and Gray models. The results show that the proposed parametric mixture method compared with other models provides consistently less biased estimates for low, mildly, moderately, and heavily censored samples. The analysis of post-kidney transplant malignancy data showed that the conclusions obtained from the mixture and other approaches have some different interpretations.

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APA: Copy

SALESI, MAHMOOD, RAHIMI FOROUSHANI, ABBAS, MOHAMMADI, JAMILE, ROSTAMI, ZOHREH, MEHRAZMAY, ALI REZA, EINOLLAHI, BEHZAD, KARAMBAKSH, ALI REZA, ASGHARIAN, SAEED, & ESHRAGHIAN, MOHAMMAD REZA. (2016). AN EXPECTATION-CONDITIONAL MAXIMIZATION-BASED WEIBULL-GOMPERTZ MIXTURE MODEL FOR ANALYZING COMPETING-RISKS DATA: USING POST-TRANSPLANT MALIGNANCY DATA. JOURNAL OF BIOSTATISTICS AND EPIDEMIOLOGY, 2(1), 1-8. SID. https://sid.ir/paper/308508/en

Vancouver: Copy

SALESI MAHMOOD, RAHIMI FOROUSHANI ABBAS, MOHAMMADI JAMILE, ROSTAMI ZOHREH, MEHRAZMAY ALI REZA, EINOLLAHI BEHZAD, KARAMBAKSH ALI REZA, ASGHARIAN SAEED, ESHRAGHIAN MOHAMMAD REZA. AN EXPECTATION-CONDITIONAL MAXIMIZATION-BASED WEIBULL-GOMPERTZ MIXTURE MODEL FOR ANALYZING COMPETING-RISKS DATA: USING POST-TRANSPLANT MALIGNANCY DATA. JOURNAL OF BIOSTATISTICS AND EPIDEMIOLOGY[Internet]. 2016;2(1):1-8. Available from: https://sid.ir/paper/308508/en

IEEE: Copy

MAHMOOD SALESI, ABBAS RAHIMI FOROUSHANI, JAMILE MOHAMMADI, ZOHREH ROSTAMI, ALI REZA MEHRAZMAY, BEHZAD EINOLLAHI, ALI REZA KARAMBAKSH, SAEED ASGHARIAN, and MOHAMMAD REZA ESHRAGHIAN, “AN EXPECTATION-CONDITIONAL MAXIMIZATION-BASED WEIBULL-GOMPERTZ MIXTURE MODEL FOR ANALYZING COMPETING-RISKS DATA: USING POST-TRANSPLANT MALIGNANCY DATA,” JOURNAL OF BIOSTATISTICS AND EPIDEMIOLOGY, vol. 2, no. 1, pp. 1–8, 2016, [Online]. Available: https://sid.ir/paper/308508/en

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