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Semi-parametric homogeneity test and sample size calculation for a two-sample problem under an inequality constraint
Journal of Statistical Planning and Inference ( IF 0.9 ) Pub Date : 2021-01-26 , DOI: 10.1016/j.jspi.2020.12.004
Guanfu Liu , Yan Fan , Yang Liu , Yukun Liu

In medical researches such as case-control studies with contaminated controls, frequently encountered is a particular two-sample testing problem in which one sample has a mixture structure. It is a very common case that the exposure in a case-control study may have a positive (or negative) effect on the response variable if the effect exists. This is often ignored by existing tests, which would lead to potentially power loss. Meanwhile, it is of much practical importance to determine a minimal sample size to reach a target power. Based on empirical likelihood and density ratio model, we develop a new EM-test by incorporating the inequality information in the alternative. We show that the proposed EM-test has a mixture of zero and χ12 limiting distribution under the null hypothesis. Its local power analysis and sample size calculations are also investigated. A simulation study and two real data analyses are provided to illustrate the proposed EM-test and sample size formula.



中文翻译:

不等式约束下两样本问题的半参数同质性检验和样本量计算

在医学研究中,例如对受污染的对照进行病例对照研究,经常遇到的是特定的两样品测试问题,其中一个样品具有混合结构。在病例对照研究中,暴露很可能对反应变量产生积极(或消极)影响(这是很常见的情况)。现有测试通常会忽略这一点,这将导致潜在的功率损耗。同时,确定最小样本量以达到目标功率具有非常重要的实践意义。基于经验似然和密度比模型,我们通过将不等式信息纳入替代方法来开发新的EM检验。我们表明,拟议的EM检验包含零和χ1个2零假设下的极限分布。还研究了其局部功效分析和样本量计算。提供了仿真研究和两次实际数据分析,以说明拟议的EM测试和样本量公式。

更新日期:2021-02-05
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