Null hypothesis tests are popularly used when there is no appropriate alternative hypothesis available, especially in model assessment, where the assumed model is evaluated with no model being considered an alternative. Motivated by a test for Clayton models in multivariate survival analysis, we propose a perturbation-based method for null hypothesis testing that makes use of the resampling approach in Jin et al. (Jin et al., Biometrika; 2001; 88, 381–390) to estimate the variance–covariance matrix of an estimator to avoid intractable variance estimation. The proposed tests are straightforward and theoretically justified. We apply the proposed method to modify the tests in Shih (Shih, Biometrika; 1998; 85, 189–200) for the assessment of Clayton models. The proposed tests present satisfactory performance in simulation studies. A colon cancer dataset further illustrates the proposed tests.

中文翻译：

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应用于克莱顿模型的基于扰动的零假设检验

当没有适当的替代假设可用时，通常使用零假设检验，特别是在模型评估中，在评估假设模型时没有将模型视为替代假设。受多变量生存分析中克莱顿模型检验的启发，我们提出了一种基于扰动的零假设检验方法，该方法利用了 Jin 等人的重采样方法。(Jin et al., Biometrika ; 2001; 88, 381-390) 来估计估计量的方差-协方差矩阵，以避免难以处理的方差估计。建议的测试简单明了，在理论上是合理的。我们应用所提出的方法来修改 Shih (Shih, Biometrika; 1998; 85, 189–200) 用于评估克莱顿模型。所提出的测试在模拟研究中表现出令人满意的性能。结肠癌数据集进一步说明了建议的测试。