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Analysis of an outcome-dependent enriched sample: hypothesis tests

机译:结果依赖型富集样本的分析:假设检验

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An outcome-dependent sample is generated by a stratified survey design where the stratification depends on the outcome. It is also known as a case-control sample in epidemiological studies and a choice-based sample in econometrical studies. An outcome-dependent enriched sample (ODE) results from combining an outcome-dependent sample with an independently collected random sample. Consider the situation where the conditional probability of a categorical outcome given its covariates follows an explicit model with an unknown parameter whereas the marginal probability of the outcome and its covariates are left unspecified. Profile-likelihood (PL) and weighted-likelihood (WL) methods have been employed to estimate the model parameter from an ODE sample. This article develops the PL- and WL-based families of tests on the model parameter from an ODE sample. Asymptotic properties of their test statistics are derived. The PL likelihood-ratio, Wald and score tests are shown to obey classical inference, i.e. their test statistics are asymptotically equivalent and Chi-squared distributed. In contrast, the WL likelihood-ratio statistic asymptotically has a weighted Chi-squared distribution and is not equivalent to the WL Wald and score statistics. Our theoretical derivation and simulation show that tests based on these new statistics carry nominal type I error and good power. Advantages of ODE sampling together with the implementation of the PL and WL methods are demonstrated in an illustrative example.
机译:通过分层调查设计生成结果依赖样本,其中分层取决于结果。在流行病学研究中,它也被称为病例对照样本;在计量经济学研究中,它被称为基于选择的样本。结果依赖型富集样本(ODE)通过将结果依赖型样本与独立收集的随机样本组合而成。考虑这样一种情况:给定协变量的分类结果的条件概率遵循带有未知参数的显式模型,而未指定结果及其协变量的边际概率。轮廓似然法(PL)和加权似然法(WL)已用于从ODE样本估计模型参数。本文针对ODE样本的模型参数开发了基于PL和WL的测试系列。得出其检验统计量的渐近性质。 PL似然比,Wald和得分测试显示服从经典推断,即它们的测试统计量渐近等效且卡方分布。相反,WL似然比统计量渐近地具有加权卡方分布,并且不等同于WL Wald和得分统计量。我们的理论推导和仿真表明,基于这些新统计数据的测试带有标称I型误差和良好的功效。在一个说明性示例中展示了ODE采样的优点以及PL和WL方法的实现。

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