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减少动物使用:实验设计与实验质量

Reduction of animal use: experimental design and quality of experiments.

作者信息

Festing M F

机构信息

MRC Toxicology Unit, University of Leicester, UK.

出版信息

Lab Anim. 1994 Jul;28(3):212-21. doi: 10.1258/002367794780681697.

Abstract

Poorly designed and analysed experiments can lead to a waste of scientific resources, and may even reach the wrong conclusions. Surveys of published papers by a number of authors have shown that many experiments are poorly analysed statistically, and one survey suggested that about a third of experiments may be unnecessarily large. Few toxicologists attempted to control variability using blocking or covariance analysis. In this study experimental design and statistical methods in 3 papers published in toxicological journals were used as case studies and were examined in detail. The first used dogs to study the effects of ethanol on blood and hepatic parameters following chronic alcohol consumption in a 2 x 4 factorial experimental design. However, the authors used mongrel dogs of both sexes and different ages with a wide range of body weights without any attempt to control the variation. They had also attempted to analyse a factorial design using Student's t-test rather than the analysis of variance. Means of 2 blood parameters presented with one decimal place had apparently been rounded to the nearest 5 units. It is suggested that this experiment could equally well have been done in 3 blocks using 24 instead of 46 dogs. The second case study was an investigation of the response of 2 strains of mice to a toxic agent causing bladder injury. The first experiment involved 40 treatment combinations (2 strains x 4 doses x 5 days) with 3-6 mice per combination. There was no explanation of how the experiment involving approximately 180 mice had actually been done, but unequal subclass numbers suggest that the experiment may have been done on an ad hoc basis rather than being properly designed. It is suggested that the experiment could have been done as 2 blocks involving 80 instead of about 180 mice. The third study again involved a factorial design with 4 dose levels of a compound and 2 sexes, with a total of 80 mice. Open field behaviour was examined. The author incorrectly used the t-test to analyse the data, and concluded that there was no dose effect, when a correct analysis showed this to be highly significant. In all case studies the scientists presented means +/- standard deviations or standard errors involving only the animals contributing to that mean, rather than the much better estimates that would be obtained with a pooled estimate of error. This is virtually a universal practice.(ABSTRACT TRUNCATED AT 400 WORDS)

摘要

设计和分析欠佳的实验可能会导致科研资源的浪费,甚至可能得出错误结论。多位作者对已发表论文的调查表明,许多实验的统计分析存在缺陷,一项调查显示约三分之一的实验规模可能过大。很少有毒理学家尝试使用区组设计或协方差分析来控制变异性。在本研究中,选取了毒理学杂志上发表的3篇论文中的实验设计和统计方法作为案例进行详细剖析。第一篇论文采用2×4析因实验设计,用狗研究长期饮酒后乙醇对血液和肝脏参数的影响。然而,作者使用了不同性别、年龄和体重范围广泛的杂种狗,却未采取任何措施控制变异性。他们还试图用学生t检验而非方差分析来分析析因设计。呈现的两个血液参数均值保留一位小数,显然是四舍五入到最接近的5个单位。有人认为,该实验用24只而非46只狗,分3个区组来做同样可行。第二个案例研究是对2种品系小鼠对一种导致膀胱损伤的有毒物质的反应进行调查。第一个实验涉及40种处理组合(2个品系×4个剂量×5天),每种组合有3至6只小鼠。对于这个涉及约180只小鼠的实验实际是如何进行的,没有任何解释,但亚组数量不均表明该实验可能是临时进行的,而非经过妥善设计。有人认为,该实验可以分成2个区组,用80只而非约180只小鼠来做。第三个研究同样涉及一个析因设计,有化合物的4个剂量水平和2种性别,共80只小鼠,研究旷场行为。作者错误地使用t检验分析数据,得出不存在剂量效应的结论,而正确分析显示剂量效应非常显著。在所有案例研究中,科学家们给出的均值±标准差或标准误仅涉及对该均值有贡献的动物,而不是通过合并误差估计能得到的更好估计值。这几乎是一种普遍做法。(摘要截选至400字)

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