Paine R R, Harpending H C
Department of Anthropology, University of Utah, Salt Lake City 84113, USA.
Am J Phys Anthropol. 1998 Feb;105(2):231-40. doi: 10.1002/(SICI)1096-8644(199802)105:2<231::AID-AJPA9>3.0.CO;2-X.
Paleodemographers must work to understand how representative any archaeologically recovered skeletal series is and the potential effects of series bias on their demographic reconstructions. We examine two forms of bias: 1) infant underenumeration caused by differential preservation or incomplete archaeological recovery and 2) the underenumeration of individuals over age 45 related to methodological bias. We generated 60 simulated skeletal series of 250 individuals each based on the Brass ([1971] Biological Aspects of Demography (London: Taylor and Francis), pp. 69-110) logit models. In the first test, age bias was introduced deterministically for all individuals with age at death over 40 years using the Lovejoy et al. ([1985] Am. J. Phys. Anthropol. 68:1-14) bias estimates. In the second test, 50% of all individuals under 5 years old were removed from each simulated distribution. The simulated series were analyzed using the model life table fitting procedure developed by the authors (Milner et al. [1989] Am. J. Phys. Anthropol. 80:49-58; Paine [1989] Am. J. Phys. Anthropol. 79:51-62). Forms of adult age estimation bias described by Lovejoy and coworkers inflate estimates by 10-20% of the true crude birth rate (CBR) (the number of births per year per 1,000 population). Overestimation of fertility and birth rates increases both absolutely and as a percentage of the true rate as population growth increases. This bias is very consistent. Because Lovejoy and colleagues have estimated the methodological bias itself, its effects can be estimated. Infant underenumeration is a more serious obstacle. It is not presently possible to estimate infant underenumeration reliably without prior knowledge of fertility rates. This reduces fertility reconstructions based on infant-biased samples to minimum fertility estimates.
古人口统计学家必须努力了解任何考古发掘出的骨骼序列具有多大的代表性，以及序列偏差对其人口结构重建的潜在影响。我们研究了两种偏差形式：1）由于保存差异或考古发掘不完整导致的婴儿漏计，以及2）与方法偏差相关的45岁以上个体的漏计。我们基于布拉斯（[1971年]《人口统计学的生物学方面》（伦敦：泰勒与弗朗西斯出版社），第69 - 110页）的对数单位模型，生成了60个模拟骨骼序列，每个序列包含250个个体。在第一次测试中，使用洛夫乔伊等人（[1985年]《美国体质人类学杂志》68卷：第1 - 14页）的偏差估计值，确定性地引入死亡年龄超过40岁的所有个体的年龄偏差。在第二次测试中，从每个模拟分布中移除所有5岁以下个体的50%。使用作者开发的模型生命表拟合程序（米尔纳等人[1989年]《美国体质人类学杂志》80卷：第49 - 58页；佩恩[1989年]《美国体质人类学杂志》79卷：第51 - 62页）对模拟序列进行分析。洛夫乔伊及其同事描述的成人年龄估计偏差形式，使真实粗出生率（CBR，即每1000人口每年的出生数）的估计值膨胀了10% - 20%。随着人口增长，生育率和出生率的高估在绝对值上以及占真实率的百分比上都有所增加。这种偏差非常一致。由于洛夫乔伊及其同事已经估计了方法偏差本身，所以可以估计其影响。婴儿漏计是一个更严重的障碍。在没有生育率先验知识的情况下，目前无法可靠地估计婴儿漏计情况。这将基于有婴儿偏差样本的生育率重建降低到最低生育率估计值。
