2016•Journal of Medical Statistics and InformaticsOpen access

Comparison of performance of exponential, Cox proportional hazards, weibull and frailty survival models for analysis of small sample size data

Christopher Stanley, ELIZABETH M. MOLYNEUX, Mavuto Mukaka

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Abstract

Introduction The Cox proportional hazards (PH) model is the most widely used approach in survival analysis of clinical trials because it requires few assumptions [1]. The model was proposed by Cox in 1972 for analysis of survival data with and without censoring; for identifying differences in survival

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Introduction The Cox proportional hazards (PH) model is the most widely used approach in survival analysis of clinical trials because it requires few assumptions [1]. The model was proposed by Cox in 1972 for analysis of survival data with and without censoring; for identifying differences in survival

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Available abstract

Introduction The Cox proportional hazards (PH) model is the most widely used approach in survival analysis of clinical trials because it requires few assumptions [1]. The model was proposed by Cox in 1972 for analysis of survival data with and without censoring; for identifying differences in survival

Key concepts: Weibull distribution, Proportional hazards model, Statistics, Survival analysis, Sample size determination, Sample (material), Exponential function, Exponential distribution

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