In this paper, a nonparametric test based on incomplete data is proposed to investigate the usual stochastic order  using an extension of Banerjee statistic for Type I censored data. This extension is optimized with weight coefficients based on Simpson's rule and the bootstrap method with 10000 iterations to estimate the empirical distribution of the proposed test statistic. The empirical distribution of the statistic under censoring is studied, and the power of the test is evaluated using Monte Carlo simulations against the Lehmann alternative model.