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Doctoral Dissertation Research: The conditional independence assumption in juvenile dental age estimation

博士论文研究：青少年牙龄估计中的条件独立假设

基本信息

批准号：
2141943
负责人：
Lyle Konigsberg
金额：
$ 0.44万
依托单位：
University of Illinois at Urbana-Champaign
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2022
资助国家：
美国
起止时间：
2022-04-01 至 2023-11-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2141943&HistoricalAwards=false
关键词：
Doctoral Dissertation Research conditional independence

项目摘要

Estimating the age of individuals based on skeletal elements can inform our understanding of human biocultural experiences, identities, and population dynamics across the history of our species. Methods that use information about dental development are particularly useful for juvenile age estimation. This doctoral dissertation research project examines the developmental relationships between teeth and how these relationships affect error rates in juvenile dental age estimation. A better understanding of human variation in dental correlations can improve both methods of age estimation for bioarchaeological and forensic research as well as clinical understanding of human growth and development. The project supports graduate training in STEM, the development of open-source dental age estimation software, and online training workshops for researchers and practitioners. In order to simplify mathematical modeling, it is often assumed that dental developmental traits are independent from one another after accounting for the effect of chronological age. The problem with this conditional independence assumption is that if conditional independence is not biologically valid, resulting age estimates will be biased and have error rates that are larger than expected. This is a problem in both bioarchaeology and forensic anthropology because biased age estimates can compromise our understanding of past populations and unknown age interval error rates do not meet the Daubert standard for expert testimony. These issues are addressed through three specific aims: 1) characterize the extent of correlations between developing teeth, 2) characterize the degree of variability of correlations between developing teeth, and 3) develop, validate, and test an open-source developmental age estimation program that incorporates the correlations between teeth. These aims are approached using Bayesian statistical models and cluster analysis in R. Models are fit to dental development scores of living children and validated using dental development scores from existing decedent databases in order to develop the age estimation software.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

根据骨骼元素估计个体的年龄可以让我们了解人类的生物文化经验，身份和我们物种历史上的人口动态。使用有关牙齿发育的信息的方法对青少年年龄估计特别有用。本博士论文研究项目探讨了牙齿之间的发育关系，以及这些关系如何影响青少年牙龄估计的错误率。更好地了解人类牙齿相关性的变化可以改善生物考古学和法医学研究的年龄估计方法以及对人类生长和发育的临床理解。该项目支持STEM研究生培训，开发开源牙龄估计软件，以及为研究人员和从业人员举办在线培训研讨会。为了简化数学建模，通常假设牙齿发育性状在考虑实际年龄的影响后彼此独立。这个条件独立假设的问题是，如果条件独立在生物学上是无效的，那么得到的年龄估计将是有偏差的，并且误差率大于预期。这在生物考古学和法医人类学中都是一个问题，因为有偏见的年龄估计会损害我们对过去人口的理解，而未知的年龄间隔错误率不符合Daubert专家证词的标准。这些问题通过三个具体目标来解决：1）表征发育中的牙齿之间的相关性程度，2）表征发育中的牙齿之间的相关性的变化程度，以及3）开发，验证和测试一个开源的发育年龄估计程序，该程序包含牙齿之间的相关性。这些目标是接近使用贝叶斯统计模型和聚类分析R。模型是适合牙齿发育分数的生活儿童和验证使用牙齿发育分数从现有的死者数据库，以开发的年龄估计software.This奖项反映了NSF的法定使命，并已被认为是值得的支持，通过评估使用基金会的智力价值和更广泛的影响审查标准。