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Re-examining the use of the LSI technique in zooarchaeology

机译:重新检查LSI技术在ZooSarchaeology中的使用

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Biometric analysis of faunal remains is crucial for estimating the age/sex composition of assemblages and exploring large-scale processes that affected animal biology in the past. The LSI technique is a premier method for examining biometry in different zooarchaeological scenarios, particularly domestication research and regional-scale surveys. Despite the technique's popularity, several early arguments describing limitations or concerns about the LSI technique still impact interpretations and applications today. More generally, though, the LSI technique is treated as a method of increasing sample sizes as a last resort when unmodified measurements are too scarce to use. This paper re-examines the theoretical foundations of the LSI technique to update best practices in LSI analyses in zooarchaeology. Redefining the LSI technique as a pseudo-centering process shows why LSI values are preferable to unmodified measurements for biometric analyses. This new definition also highlights the arbitrary nature of standard animal and logarithm base choice, though certain decisions (smaller standard animals and base e logarithms) can aid interpretation by closely linking changes in LSI values to proportional changes of the original measurements relative to the standard. Of more consequence on LSI ana-lyses, however, is the way to aggregate LSI values from different measurement types; this paper shows how multilevel modeling uses partial pooling to balance the trade-offs of bias and variance caused by aggregation. To showcase the benefits of the Bayesian multilevel LSI model, the biometric variation of ten simulated sites using a reference set of Shetland sheep measurements (Popkin Peter et al., 2012). Modeling all ten sites within a single multilevel structure provides a clear way to evaluate biometric differences while accounting for potential allometries and variation in body part representation between different sites. These results clarify earlier arguments about the limitations of the LSI technique, summarized in a set of best practices for LSI applications.
机译:对动物遗骸的生物特征分析对于估计集合的年龄/性别组成和探索过去影响动物生物学的大规模过程至关重要。LSI技术是在不同的动物考古场景中检查生物测量学的主要方法,尤其是驯化研究和区域规模调查。尽管这种技术很受欢迎,但描述LSI技术局限性或担忧的几个早期论点仍然影响着今天的解释和应用。不过,更一般地说,当未经修改的测量数据太少而无法使用时,LSI技术被视为增加样本量的最后手段。本文重新审视了LSI技术的理论基础,以更新动物考古学中LSI分析的最佳实践。将LSI技术重新定义为伪定心过程,说明了为什么LSI值比生物特征分析的未修改测量值更可取。这一新定义还强调了标准动物和对数基数选择的任意性,尽管某些决定(较小的标准动物和e基数对数)可以通过将LSI值的变化与原始测量值相对于标准的比例变化紧密联系起来来帮助解释。然而,对LSI分析更重要的是,从不同测量类型中聚合LSI值的方法;本文展示了多层次建模如何使用部分池来平衡由聚合引起的偏差和方差。为了展示贝叶斯多级LSI模型的优点,我们使用设得兰羊测量的参考集对十个模拟地点进行了生物特征变化(Popkin-Peter等人,2012年)。在一个多级结构中对所有十个部位进行建模,为评估生物特征差异提供了一种清晰的方法,同时考虑了不同部位之间身体部位表征的潜在差异和变化。这些结果澄清了早期关于LSI技术局限性的争论,总结在一组LSI应用的最佳实践中。

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