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[医学研究中统计检验的持续发展]

[Continuing evolution of statistical tests in medical research].

作者信息

Totaro Angelo, Volpe Andrea, Sacco Emilio, Pinto Francesco, Palma Monica, Bassi Pierfrancesco

机构信息

Clinica Urologica, Università Cattolica del Sacro Cuore, Roma, Italy.

出版信息

Urologia. 2010 Oct-Dec;77(4):232-9.

Abstract

The role of statistics in medical research starts at the planning stage of a clinical trial or laboratory experiment to establish the design and size of an experiment that will ensure a good prospect of detecting effects of clinical or scientific interest. Statistics is again used during data analysis (sample data) to make inferences valid in a wider population. In simple situations, computation of simple quantities such as P-values, confidence intervals, standard deviations, standard errors or application of some standard parametric or nonparametric tests may suffice. Moreover, despite the wide use of statistics in medical research, simple notions are sometimes misunderstood or misinterpreted by medical research workers, who have only a limited knowledge of statistics. This article, written for non-statisticians, is to explain what are the most common statistical tests used today in the field of medical research, tracing the evolution of statistical tests over time, in particular the introduction of nonparametric methods and, more recently, the NonParametric Combination (NPC) methodology. At the same time, this work seeks to identify some of the errors associated with their use, that often lead to an incorrect assessment and interpretation of results of medical research.

摘要

统计学在医学研究中的作用始于临床试验或实验室实验的规划阶段,以确定实验的设计和规模,确保有良好的前景来检测具有临床或科学意义的效应。在数据分析(样本数据)过程中,统计学再次被用于做出在更广泛人群中有效的推断。在简单情况下,计算诸如P值、置信区间、标准差、标准误差等简单量,或应用一些标准的参数或非参数检验可能就足够了。此外,尽管统计学在医学研究中被广泛使用,但一些简单概念有时会被医学研究人员误解或错误解读,因为他们对统计学的了解有限。本文是为非统计学家撰写的,旨在解释当今医学研究领域最常用的统计检验方法,追溯统计检验方法随时间的演变,特别是非参数方法的引入,以及最近的非参数组合(NPC)方法。同时,这项工作旨在识别与这些方法使用相关的一些错误,这些错误常常导致对医学研究结果的错误评估和解读。

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