Abstract

The test of Yang and Prentice, based on the short-term and long-term hazard ratio model for the presence of a regression effect appears to be an attractive one, being able to detect departures from a null hypothesis of no effect against quite broad alternatives. We recall the model on which this test is based and the test itself. In simulations, the test has shown good performance and is judged to be of potential value when alternatives to the null may be of a nonproportional hazards nature. However, the model, even when valid, suffers from a parameterization inconsistency in the sense that parameter estimates can violate the model’s assumed parametric structure even when true. This leads to awkward behavior in some situations. For example, this inconsistency implies that inference will not be invariant to the coding of treatment allocation. While this is a theoretical observation, we provide real examples that highlight the difficulty in making clear cut inferences from the model. Potential solutions are available and we provide some discussion on this.

摘要

Yang 和 Prentice 的测试基于短期和长期风险比模型对回归效应的存在似乎很有吸引力，能够检测对相当广泛的替代方案没有影响的零假设的偏离. 我们回忆一下这个测试所基于的模型和测试本身。在模拟中，该测试显示出良好的性能，并且当零值的替代方案可能具有非比例危险性质时，该测试被认为具有潜在价值。然而，即使模型有效，也存在参数化不一致的问题，即参数估计值可能违反模型假设的参数结构，即使是正确的。在某些情况下，这会导致尴尬的行为。例如，这种不一致意味着推理不会对治疗分配的编码保持不变。虽然这是一个理论观察，但我们提供了真实的例子，强调了从模型中做出明确推断的困难。可以使用潜在的解决方案，我们对此进行了一些讨论。