Robinson Chris, Terhune Claire E
Department of Biological Sciences, Bronx Community College (CUNY), Bronx, New York, 10453.
Department of Anthropology, University of Arkansas, Fayetteville, Arkansas.
Am J Phys Anthropol. 2017 Sep;164(1):62-75. doi: 10.1002/ajpa.23257. Epub 2017 Jun 2.
This study compares two- and three-dimensional morphometric data to determine the extent to which intra- and interobserver and intermethod error influence the outcomes of statistical analyses.
Data were collected five times for each method and observer on 14 anthropoid crania using calipers, a MicroScribe, and 3D models created from NextEngine and microCT scans. ANOVA models were used to examine variance in the linear data at the level of genus, species, specimen, observer, method, and trial. Three-dimensional data were analyzed using geometric morphometric methods; principal components analysis was employed to examine how trials of all specimens were distributed in morphospace and Procrustes distances among trials were calculated and used to generate UPGMA trees to explore whether all trials of the same individual grouped together regardless of observer or method.
Most variance in the linear data was at the genus level, with greater variance at the observer than method levels. In the 3D data, interobserver and intermethod error were similar to intraspecific distances among Callicebus cupreus individuals, with interobserver error being higher than intermethod error. Generally, taxa separate well in morphospace, with different trials of the same specimen typically grouping together. However, trials of individuals in the same species overlapped substantially with one another.
Researchers should be cautious when compiling data from multiple methods and/or observers, especially if analyses are focused on intraspecific variation or closely related species, as in these cases, patterns among individuals may be obscured by interobserver and intermethod error. Conducting interobserver and intermethod reliability assessments prior to the collection of data is recommended.
本研究比较二维和三维形态测量数据,以确定观察者内和观察者间误差以及方法间误差对统计分析结果的影响程度。
使用卡尺、三维数字化仪以及由NextEngine和显微CT扫描创建的三维模型,对14个类人猿颅骨,针对每种方法和观察者各收集5次数据。采用方差分析模型,在属、种、标本、观察者、方法和试验水平上检验线性数据的方差。使用几何形态测量方法分析三维数据;采用主成分分析来研究所有标本的试验在形态空间中的分布情况,并计算试验间的普氏距离,用于生成加权组平均法树状图,以探索同一标本的所有试验是否无论观察者或方法如何都聚集在一起。
线性数据中的大部分方差存在于属水平,观察者水平的方差大于方法水平。在三维数据中,观察者间和方法间误差与铜头伶猴个体的种内距离相似,观察者间误差高于方法间误差。一般来说,分类单元在形态空间中区分良好,同一标本的不同试验通常聚集在一起。然而,同一物种个体的试验彼此之间有大量重叠。
研究人员在汇编来自多种方法和/或观察者的数据时应谨慎,特别是当分析集中在种内变异或近缘物种时,因为在这些情况下,个体间的模式可能会被观察者间和方法间误差所掩盖。建议在收集数据之前进行观察者间和方法间的可靠性评估。