首页> 外文期刊>The Journal of Clinical Pharmacology: Official Journal of the American College of Clinical Pharmacology >Independence and statistical inference in clinical trial designs: a tutorial review.
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Independence and statistical inference in clinical trial designs: a tutorial review.

机译:临床试验设计中的独立性和统计推断:教程复习。

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摘要

The requirements for statistical approaches to the design, analysis, and interpretation of experimental data are now accepted by the scientific community. This is of particular importance in medical studies where public health consequences are of concern. Investigators in the clinical sciences should be cognizant of statistical principles in general, but should always be wary of the pursuing their own analyses and engage statisticians for data analysis whenever possible. Examples of circumstances that require statistical evaluation not found in textbooks and not always obvious to the lay person are pervasive. Incorrect statistical evaluation and analyses in such situations will result in erroneous and potentially serious misleading interpretation of clinical data. Although a statistician may not be responsible for any misinterpretations in such unfortunate circumstances, the quote often cited about statisticians and "damned liars" may appear to be more truth than fable. This article is a tutorial review and describes a common misuse of clinical data resulting in an apparently large sample size derived from a small number of patients. This mistake is a consequence of ignoring the dependency of results, treating multiple observations from a single patient as independent observations.
机译:现在,科学界已经接受了对设计,分析和解释实验数据的统计方法的要求。这在关注公共卫生后果的医学研究中尤为重要。一般而言,临床科学的研究人员应该对统计原理有所了解,但应始终提防自己进行分析,并尽可能让统计学家进行数据分析。要求教科书中没有统计评估并且对外行人并不总是显而易见的情况的例子无处不在。在这种情况下,不正确的统计评估和分析将导致对临床数据的错误甚至潜在的严重误导性解释。尽管在这种不幸的情况下统计学家可能不对任何误解负责,但经常引用的关于统计学家和“该死的骗子”的话似乎比寓言更真实。本文是一篇教程综述,并描述了临床数据常见的误用,导致从少数患者那里获得的样本量显然很大。该错误是由于忽略了结果的依赖性,将来自单个患者的多个观察结果视为独立观察结果而导致的。

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