块(置换群论)
混淆
讨厌的人
计量经济学
计算机科学
统计
风险分析(工程)
医学
数学
几何学
政治学
法学
作者
A. Eric Schultze,Bindu Bennet,Jessica Caverly Rae,Alan Y. Chiang,Kendall S. Frazier,Paula Katavolos,LuAnn McKinney,Daniel J. Patrick,Niraj Tripathi
标识
DOI:10.1177/0192623320906385
摘要
Detection of test article-related effects and the determination of the adversity of those changes are the primary goals of nonclinical safety assessment studies for drugs and chemicals in development. During these studies, variables that are not of primary interest to investigators may change and influence data interpretation. These variables, often referred to as "nuisance factors," may influence other groups of data and result in "block or batch effects" that complicate data interpretation. Definitions of the terms "nuisance factors," "block effects," and "batch effects," as they apply to nonclinical safety assessment studies, are reviewed. Multiple case examples of block and batch effects in safety assessment studies are provided, and the challenges these bring to pathology data interpretation are discussed. Methods to mitigate the occurrence of block and batch effects in safety assessment studies, including statistical blocking and utilization of study designs that minimize potential confounding variables, incorporation of adequate randomization, and use of an appropriate number of animals or repeated measurement of specific parameters for increased precision, are reviewed. [Box: see text].
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