Mitchell C L
Ann N Y Acad Sci. 1976;281:118-35. doi: 10.1111/j.1749-6632.1976.tb27925.x.
It was pointed out that all fields of biological research have one feature common: inherent variability. Since this is the case and since it is not feasible to examine the entire population one is interested in, the experimenter is forced to give probability statements concerning any treatment differences observed. In order to do this, it is necessary for the experiment to be designed in such a way that a statistical analysis of the data will yield a valid answer to the question, "What is the probability that the differences observed could have occurred by chance?" The importance of randomization in the selection of the samples was emphasized. The problem of determining the sample size was discussed in relation to Type I (rejecting the null hypothesis when it is true) and Type II (accepting the null hypothesis when it is false) errors. It was suggested that too little attention is given to the possibility of Type II errors in biological research. It was emphasized that the specific question, or questions, one is asking should be precisely formulated prior to the design of the experiment, since hazily formulated ideas are difficult to discuss and virtually impossible to test for correctness. Once the experiment has been designed, both the questions and the design should be critically and logically evaluated for any fallacies. If the investigator has any doubts about the design or the manner in which the data will be analyzed, a statistician should be consulted before the experiment is conducted. A statistician cannot extract meaningful results from data collected with a faulty design. It was emphasized that it is important to know both the dose effect and time effect of each substance on the responses to be measured, in order to provide a rationale for the doses used in the interaction studies and the time after dosing at which the effect is to be measured. The design of drug interaction experiments is based, in part, on whether or not both substances when given alone affect the response. If both substances are active, one determines the potency of one substance relative to the other in affecting the response. This can be done for either quantitative or quantal data. Once the relative potency has been determined, subsequent studies involve combining fractional doses of the substances and comparing the results against those obtained using standard doses of the substances individually. Doses of the combination and the single substances are picked such that equivalent responses should be obtained if the effect of the two together is additive. The null hypothesis is that the two compounds behave as though they were different forms of the same substance, one of which is possibly (depending on the potency ratio) diluted with an inert substance. Equivalence of response can be tested using such parametric tests as Student's t or analysis of variance (or their nonparametric equivalents) for quantitative data. Additivity is inferred if the null hypothesis is accepted...
有人指出,生物学研究的所有领域都有一个共同特征:内在变异性。既然如此,而且检查感兴趣的整个总体并不可行,实验者就不得不对观察到的任何处理差异给出概率陈述。为了做到这一点,实验设计必须使得对数据进行统计分析能够对“观察到的差异偶然出现的概率是多少?”这个问题给出有效的答案。强调了随机化在样本选择中的重要性。讨论了确定样本量的问题与I类错误(在原假设为真时拒绝原假设)和II类错误(在原假设为假时接受原假设)的关系。有人认为在生物学研究中对II类错误的可能性关注太少。强调在实验设计之前应精确地提出所问的一个或多个具体问题,因为模糊表述的想法难以讨论,实际上也无法检验其正确性。一旦设计了实验,就应对问题和设计进行批判性和逻辑性评估,以查找任何谬误。如果研究者对设计或数据分析方式有任何疑问,在进行实验之前应咨询统计学家。统计学家无法从设计有缺陷的数据中提取有意义的结果。强调了解每种物质对要测量的反应的剂量效应和时间效应很重要,以便为相互作用研究中使用的剂量以及测量效应的给药后时间提供理论依据。药物相互作用实验的设计部分基于单独给予两种物质时是否都会影响反应。如果两种物质都有活性,则要确定一种物质相对于另一种物质在影响反应方面的效力。这对于定量或定性数据都可以做到。一旦确定了相对效力,后续研究就包括将物质的分剂量组合起来,并将结果与分别使用标准剂量的物质所获得的结果进行比较。选择组合物质和单一物质的剂量,以便如果两者共同作用的效果是相加的,就应获得等效反应。原假设是这两种化合物的行为就好像它们是同一物质的不同形式,其中一种可能(取决于效力比)用惰性物质稀释。对于定量数据,可以使用诸如学生t检验或方差分析(或其非参数等效方法)等参数检验来检验反应的等效性。如果接受原假设,则推断为相加性……