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Trend tests for the evaluation of exposure-response relationships in epidemiological exposure studies

机译:在流行病学暴露研究中评估暴露-反应关系的趋势测试

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One possibility for the statistical evaluation of trends in epidemiological exposure studies is the use of a trend test for data organized in a 2 × k contingency table. Commonly, the exposure data are naturally grouped or continuous exposure data are appropriately categorized. The trend test should be sensitive to any shape of the exposure-response relationship. Commonly, a global trend test only determines whether there is a trend or not. Once a trend is seen it is important to identify the likely shape of the exposure-response relationship. This paper introduces a best contrast approach and an alternative approach based on order-restricted information criteria for the model selection of a particular exposure-response relationship. For the simple change point alternative H 1 : π 1 = ...= π q π q +1 = ... = π k an appropriate approach for the identification of a global trend as well as for the most likely shape of that exposure-response relationship is characterized by simulation and demonstrated for real data examples. Power and simultaneous confidence intervals can be estimated as well. If the conditions are fulfilled to transform the exposure-response data into a 2 × k table, a simple approach for identification of a global trend and its elementary shape is available for epidemiologists.
机译:对流行病学暴露研究趋势进行统计评估的一种可能性是,对以2×k列联表进行组织的数据进行趋势检验。通常,将曝光数据自然地分组或将连续的曝光数据适当地分类。趋势测试应该对任何形式的曝光-响应关系敏感。通常,全局趋势测试仅确定是否存在趋势。一旦发现趋势,识别暴露-响应关系的可能形状就很重要。本文介绍了一种最佳对比方法和一种基于顺序受限信息标准的替代方法,用于特定暴露-响应关系的模型选择。对于简单的更改点,替代H 1 :π 1 = ... =π< sub class =“ a-plus-plus”> q π q +1 = ... =π k 是一种识别全局趋势以及最可能的暴露-响应关系形状的合适方法,通过仿真进行了描述,并针对实际数据示例进行了演示。功效和同时置信区间也可以估算。如果满足将暴露响应数据转换为2×k表的条件,则流行病学家可以使用一种简单的方法来识别全球趋势及其基本形状。

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