Abstract
We consider a variety of tests for testing goodness–of–fit in a parametric Cox proportional hazards (PH) and accelerated failure time (AFT) model in the presence of Type–II right censoring. The testing procedures considered can be divided in two categories: an approach involving transforming the data to a complete sample and an approach using test statistics that can directly accommodate Type-II right censoring. The power of the proposed tests are compared through a Monte Carlo study for various scenarios. It is found that both approaches are useful for testing exponentiality if the censoring proportion in a data set is lower than 30%, but that it is recommended to use the approach that first transforms the sample to a complete sample when one encounters higher censoring proportions.
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