Nonparametric Analysis of an Accelerated Failure Time Model
Copyright policy )Nonparametric Analysis of an Accelerated Failure Time Model
SUMMARY Survival distributions can be characterized by and compared through their hazard functions. Tests using a proportional hazards model have good power if the two hazards do not cross, but without time-dependent covariates can have low power if they do. The method contained herein is designed to provide a complement to the proportional hazards model. Differences in survival distributions are parameterized by a scale change and the log rank statistic is used to generate an estimate of the change and a confidence interval based test. This approach is fully efficient for the Weibull family with no censoring. In general it compares favourably with the proportional hazards approach, although neither method dominates.
- Harvard University United States
log rank statistic, Reliability and life testing, scale change alternative, Weibull family, survival distributions, proportional hazards, Applications of statistics to biology and medical sciences; meta analysis, accelerated failure time model, censored data, Nonparametric hypothesis testing, regression-life model
log rank statistic, Reliability and life testing, scale change alternative, Weibull family, survival distributions, proportional hazards, Applications of statistics to biology and medical sciences; meta analysis, accelerated failure time model, censored data, Nonparametric hypothesis testing, regression-life model
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