Martinez Marilyn N, Bartholomew Mary J
Office of New Animal Drug Evaluation, Center for Veterinary Medicine, US FDA, Rockville, MD 20855, USA.
Office of Surveillance and Compliance, Center for Veterinary Medicine, US FDA, Rockville, MD 20855, USA.
Pharmaceutics. 2017 Apr 13;9(2):14. doi: 10.3390/pharmaceutics9020014.
Typically, investigations are conducted with the goal of generating inferences about a population (humans or animal). Since it is not feasible to evaluate the entire population, the study is conducted using a randomly selected subset of that population. With the goal of using the results generated from that sample to provide inferences about the true population, it is important to consider the properties of the population distribution and how well they are represented by the sample (the subset of values). Consistent with that study objective, it is necessary to identify and use the most appropriate set of summary statistics to describe the study results. Inherent in that choice is the need to identify the specific question being asked and the assumptions associated with the data analysis. The estimate of a "mean" value is an example of a summary statistic that is sometimes reported without adequate consideration as to its implications or the underlying assumptions associated with the data being evaluated. When ignoring these critical considerations, the method of calculating the variance may be inconsistent with the type of mean being reported. Furthermore, there can be confusion about why a single set of values may be represented by summary statistics that differ across published reports. In an effort to remedy some of this confusion, this manuscript describes the basis for selecting among various ways of representing the mean of a sample, their corresponding methods of calculation, and the appropriate methods for estimating their standard deviations.
通常情况下，开展调查的目的是对总体（人类或动物）进行推断。由于评估整个总体是不可行的，因此研究是使用从该总体中随机选取的一个子集来进行的。为了利用从该样本得出的结果对真实总体进行推断，考虑总体分布的特性以及样本（值的子集）对这些特性的代表程度是很重要的。与该研究目标一致，有必要识别并使用最合适的一组汇总统计量来描述研究结果。在做出该选择时，内在要求是识别所提出的具体问题以及与数据分析相关的假设。“均值”的估计就是一个汇总统计量的例子，有时在报告时没有充分考虑其含义或与所评估数据相关的潜在假设。当忽略这些关键因素时，方差的计算方法可能与所报告的均值类型不一致。此外，对于为什么一组值可能由不同发表报告中的汇总统计量来表示，可能会存在困惑。为了消除其中一些困惑，本手稿描述了在表示样本均值的各种方式中进行选择的依据、它们相应的计算方法以及估计其标准差的合适方法。
