Censored regression models are commonly used in statistics, but their hypothesis tests often rely on unknown error distributions. A new method called randomly weighting test statistic has been developed to approximate the null distribution of these tests without needing to estimate nuisance parameters. This method shows consistent results and performs better than traditional approaches in simulation studies.