Non-parametric hypothesis testing to model some cancers based on goodness of fit

Abstract

By observing the failure behavior of the recorded survival data, we aim to compare the different processing approaches or the effectiveness of the devices or systems applied in this non-parametric statistical test. We'll apply the proposed strategy of used better than aged in Laplace (UBAL) transform order, which assumes that the data used in the test will either behave as UBAL Property or exponential behavior. If the survival data is UBAL, it means that the suggested treatment strategy is effective, whereas if the data is exponential, the recommended treatment strategy has no negative or positive effect on patients, as indicated in the application section. To guarantee the test's validity, we calculated the suggested test's power in both censored and uncensored data, as well as its efficiency, compared the results to other tests, and then applied the test to a variety of real data.

Keywords

• testing hypothesis
• right censored data
• exponential
• weibull
• gamma
• makeham and linear failure rate (lfr) distributions
• uba and ubal classes of life distributions
• medical data