Rc. Tiwari et Jn. Zalkikar, TESTING CONSTANT FAILURE RATE AGAINST NBAFR ALTERNATIVES WITH RANDOMLY RIGHT-CENSORED DATA, IEEE transactions on reliability, 43(4), 1994, pp. 634-639
Reliability analysts and biometricians have found it useful to categor
ize Life distributions by the properties of the failure rate. This pap
er considers the problem of testing exponentiality vs (non exponential
) new better than average failure rate (NBAFR) alternatives. Often, in
practice, the data are incomplete because of: a) withdrawals from the
study, and b) survivors at the time the data are analyzed. We propose
a test statistic based on a function of the Kaplan-Meier estimator to
accommodate randomly right censored data. The asymptotic efficacy of
the test is derived and the efficiency loss due to censoring is studie
d. Our test is applied to published survival data, and to simulated da
ta.