Piriform apertures from skulls in the Bass Collection at the University of Tennessee were examined. The morphology of the perform aperture from digital images was captured using Adobe Measuring Tool 9.0 and data analy...Piriform apertures from skulls in the Bass Collection at the University of Tennessee were examined. The morphology of the perform aperture from digital images was captured using Adobe Measuring Tool 9.0 and data analyzed with SPSS 17.0. Twenty-four linear measurements from a central point of the aperture as well as the perimeter were evaluated to quantify a difference between Black and White populations. The statistical analyses employed Discriminate Functional Analysis followed by Stepwise analysis. Discriminate functions were generated to predict to which group a skull belonged. A discriminate function produced an accuracy of 77.4%. Step-wise discriminate function analysis, using only three variables, produced an accuracy of 79.0%.展开更多
Evaluation of method performance involves the consideration of numerous factors that can contribute to error.A variety of measures of performance can be borrowed from the signal detection literature and others are dra...Evaluation of method performance involves the consideration of numerous factors that can contribute to error.A variety of measures of performance can be borrowed from the signal detection literature and others are drawn from statistical science.This article demonstrates the principles of performance evaluation by applying multiple measures to osteometric sorting models for paired elements run against data from known individuals.Results indicate that false positive rates are close,on average,to expected values.As assemblage size grows,the false positive rate becomes unimportant and the false negative rate becomes significant.Size disparity among the commingled individuals plays a significant role in method performance,showing that case-specific circumstances(e.g.assemblage size and size disparity)will determine method power.展开更多
文摘Piriform apertures from skulls in the Bass Collection at the University of Tennessee were examined. The morphology of the perform aperture from digital images was captured using Adobe Measuring Tool 9.0 and data analyzed with SPSS 17.0. Twenty-four linear measurements from a central point of the aperture as well as the perimeter were evaluated to quantify a difference between Black and White populations. The statistical analyses employed Discriminate Functional Analysis followed by Stepwise analysis. Discriminate functions were generated to predict to which group a skull belonged. A discriminate function produced an accuracy of 77.4%. Step-wise discriminate function analysis, using only three variables, produced an accuracy of 79.0%.
文摘Evaluation of method performance involves the consideration of numerous factors that can contribute to error.A variety of measures of performance can be borrowed from the signal detection literature and others are drawn from statistical science.This article demonstrates the principles of performance evaluation by applying multiple measures to osteometric sorting models for paired elements run against data from known individuals.Results indicate that false positive rates are close,on average,to expected values.As assemblage size grows,the false positive rate becomes unimportant and the false negative rate becomes significant.Size disparity among the commingled individuals plays a significant role in method performance,showing that case-specific circumstances(e.g.assemblage size and size disparity)will determine method power.
