DFG Center for Advanced Studies 'Words, Bones, Genes, Tools', University of Tübingen, 72070, Tübingen, Germany.
Paleoanthropology, Department of Geosciences, Institute for Archaeological Sciences, University of Tübingen, 72070, Tübingen, Germany.
Sci Rep. 2024 Nov 12;14(1):27713. doi: 10.1038/s41598-024-76231-1.
Traumatic lesions on human skeletal remains are widely used for reconstructing past accidents or violent encounters and for comparing trauma prevalence across samples over time and space. However, uncertainties in trauma prevalence estimates increase proportionally with decreasing skeletal completeness, as once-present trauma might have gone missing. To account for this bias, samples are typically restricted to skeletal remains meeting a predefined minimum completeness threshold. However, the effect of this common practice on resulting estimates remains unexplored. Here, we test the performance of the conventional frequency approach, which considers only specimens with ≥ 75% completeness, against a recent alternative based on generalized linear models (GLMs), integrating specimen completeness as a covariate. Using a simulation framework grounded on empirical forensic, clinical, and archaeological data, we evaluated how closely frequency- and GLM-based estimates conform to the known trauma prevalence of once-complete cranial samples after introducing increasing levels of missing values. We show that GLM-based estimates were consistently more precise than frequencies across all levels of incompleteness and regardless of sample size. Unlike GLMs, frequencies increasingly produced incorrect relative patterns between samples and occasionally failed to produce estimates as incompleteness increased, particularly in smaller samples. Consequently, we generally recommend using GLMs and their extensions over frequencies, although neither approach is fully reliable when applied to largely incomplete samples.
人体骨骼遗骸上的创伤性病变被广泛用于重建过去的事故或暴力遭遇，并比较不同时间和空间的样本中创伤的流行程度。然而，随着骨骼完整度的降低，创伤流行率的估计不确定性会成比例增加，因为曾经存在的创伤可能已经消失。为了解决这个偏差，样本通常被限制在满足预定最小完整度阈值的骨骼遗骸上。然而，这种常见做法对结果估计的影响仍未得到探索。在这里，我们测试了传统频率方法的性能，该方法仅考虑完整性≥75%的标本，以及最近基于广义线性模型（GLMs）的替代方法，该方法将标本完整性作为协变量进行整合。我们使用基于经验法医、临床和考古数据的模拟框架，评估了在引入越来越多的缺失值后，基于频率和 GLM 的估计值与曾经完整的颅骨样本的已知创伤流行率的吻合程度。我们表明，基于 GLM 的估计值在所有不完整程度下都比频率更精确，并且与样本大小无关。与 GLMs 不同，频率在不完整程度增加时，越来越多地产生了样本之间不正确的相对模式，并且偶尔会因不完整程度增加而无法产生估计值，尤其是在较小的样本中。因此，我们通常建议使用 GLMs 及其扩展而不是频率，尽管当应用于大部分不完整的样本时，这两种方法都不完全可靠。
