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A comparison of several methods to test for the existence of a monotonic dose-response relationship in clinical and epidemiological studies.

机译:临床和流行病学研究中用于测试单调剂量-反应关系是否存在的几种方法的比较。

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The Mantel-extension chi-square test for overall trend and an asymptotically equivalent test based on logistic regression are commonly used to test for a monotonic dose-response relationship between exposure and disease in epidemiological and clinical studies. However, these tests present two important disadvantages, as they (i) make the restrictive assumption of a parametric model of linear form on the logit scale and (ii) impose the a priori choice of scores to code for the exposure categories. Indeed, the linear assumption, if made incorrectly, can lead to an invalid conclusion, and the choice of scores lends arbitrariness to the test results. Some alternative tests have been proposed in the literature. We have considered several of these tests, namely one based on isotonic regression, the T-test based on contrasts and a recently published test based on adjacent contrasts (Dosemeci-Benichou test). The aim of our study was to compare the statistical properties (type I error and power) of these tests and of the commonly used Mantel-extension test for overall trend. We generated cohort and case-control data and considered one- and two-sided versions of the tests. Moreover, we studied the tests under the null hypothesis of no relationship between exposure and disease and under various alternative patterns of monotonic or non-monotonic dose-response relationships. This study confirms that the commonly used trend tests can lead to erroneous conclusion of a monotonic dose-response relationship. The test based on isotonic regression does not represent a favourable alternative, as it tends to be too powerful in case of non-monotonic dose-response relationship patterns. The tests based on contrasts seem to possess more favourable properties by combining close to nominal type I error, high power for monotonic alternatives and low power for non-monotonic alternatives. Copyright 2001 John Wiley & Sons, Ltd.
机译:在流行病学和临床研究中,通常使用Mantel扩展卡方检验和总趋势的渐近等效检验来检验暴露与疾病之间的单调剂量反应关系。但是,这些测试存在两个重要的缺点,因为它们(i)对对数刻度进行线性形式参数模型的限制性假设,并且(ii)对得分进行优先选择以对暴露类别进行编码。的确,如果线性假设不正确,则会导致无效的结论,分数的选择会给测试结果带来任意性。文献中提出了一些替代测试。我们考虑了其中几种测试,即基于等渗回归的测试,基于对比的T检验和最近发布的基于相邻对比的测试(Dosemeci-Benichou检验)。我们研究的目的是比较这些测试的统计特性(I型错误和功效)和总体趋势常用的Mantel扩展测试。我们生成了队列和病例对照数据,并考虑了测试的一侧和两侧版本。而且,我们在暴露与疾病之间没有关系的零假设下以及在单调或非单调剂量-反应关系的各种替代模式下研究了检验。这项研究证实,常用的趋势测试可能导致单调剂量反应关系的错误结论。基于等渗回归的测试并不代表一种理想的选择,因为在非单调的剂量反应关系模式下,该测试往往过于强大。通过对比接近I型误差,单调替代方案的高功率和非单调替代方案的低功率,基于对比的测试似乎具有更有利的性能。版权所有2001 John Wiley&Sons,Ltd.

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