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Brief communication: The relation between standard error of the estimate and sample size of histomorphometric aging methods

机译:简述:估计的标准误与组织形态计量学老化方法的样本量之间的关系

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摘要

Histomorphometric aging methods report varying degrees of precision, measured through Standard Error of the Estimate (SEE). These techniques have been developed from variable samples sizes (n) and the impact of n on reported aging precision has not been rigorously examined in the anthropological literature. This brief communication explores the relation between n and SEE through a review of the literature (abstracts, articles, book chapters, theses, and dissertations), predictions based upon sampling theory and a simulation. Published SEE values for age prediction, derived from 40 studies, range from 1.51 to 16.48 years (mean 8.63; sd: 3.81 years). In general, these values are widely distributed for smaller samples and the distribution narrows as n increases-a pattern expected from sampling theory. For the two studies that have samples in excess of 200 individuals, the SEE values are very similar (10.08 and 11.10 years) with a mean of 10.59 years. Assuming this mean value is a 'true' characterization of the error at the population level, the 95% confidence intervals for SEE values from samples of 10, 50, and 150 individuals are on the order of ±4.2, 1.7, and 1.0 years, respectively. While numerous sources of variation potentially affect the precision of different methods, the impact of sample size cannot be overlooked. The uncertainty associated with SEE values derived from smaller samples complicates the comparison of approaches based upon different methodology and/or skeletal elements. Meaningful comparisons require larger samples than have frequently been used and should ideally be based upon standardized samples.
机译:组织形态学老化方法报告了不同程度的精度,这些精度通过估算的标准误差(SEE)进行测量。这些技术是从可变的样本量(n)中开发出来的,并且在人类学文献中尚未严格检查n对报告的老化精度的影响。这段简短的交流通过回顾文献(摘要,文章,书中的章节,论文和学位论文),基于采样理论的预测和模拟来探索n与SEE之间的关系。来自40项研究的已发布SEE年龄预测值范围为1.51至16.48岁(平均8.63;标准差:3.81岁)。通常,这些值在较小的样本中分布广泛,并且随着n的增加而分布变窄-这是采样理论所期望的模式。对于两个样本超过200个人的研究,SEE值非常相似(10.08和11.10年),平均值为10.59年。假设此平均值是总体水平上误差的“真实”特征,那么10、50和150个人的SEE值的95%置信区间为±4.2、1.7和1.0年,分别。尽管众多变异来源可能会影响不同方法的精度,但样本量的影响却不可忽视。与源自较小样本的SEE值相关的不确定性使基于不同方法和/或骨骼元素的方法的比较复杂化。有意义的比较需要比经常使用的样本更大的样本,并且理想情况下应该基于标准化样本。

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