Comparison of hypertabastic survival model with other unimodal hazard rate functions using a goodness-of-fit test.
We studied the problem of testing a hypothesized distribution in survival regression models when the data is right censored and survival times are influenced by covariates. A modified chi-squared type test, known as Nikulin-Rao-Robson statistic, is applied for the comparison of accelerated failure time models. This statistic is used to test the goodness-of-fit for hypertabastic survival model and four other unimodal hazard rate functions. The results of simulation study showed that the hypertabastic distribution can be used as an alternative to log-logistic and log-normal distribution. In statistical modeling, because of its flexible shape of hazard functions, this distribution can also be used as a competitor of Birnbaum-Saunders and inverse Gaussian distributions. The results for the real data application are shown. Copyright © 2017 John Wiley & Sons, Ltd.
Department of Experimental Medicine, McGill University, Montreal, Canada.
M Ramzan
0000-0002-3962-6444
MR
Tahir
Faculty of Foundation Studies, Thai Binh University, Vietnam.
Quang X
QX
Tran
Faculty of Foundation Studies, Thai Binh University, Vietnam.|Institute of Mathematics of Bordeaux, University of Bordeaux, France.
Mikhail S
MS
Nikulin
D016009:Chi-Square Distribution; D006801:Humans; D016015:Logistic Models; D015233:Models, Statistical; D016011:Normal Distribution; D016016:Proportional Hazards Models; D016019:Survival Analysis
accelerated failure time models; goodness-of-fit test; hypertabastic survival model; unimodal hazard rate functions