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                            Library & Multimedia
 Significance of Association in Tool Mark Characterization
NCJ Number
              243319

Author(s)
          L. S. Chumbley;
                        M. Morris
Date Published

August 2013
Length
              54 pages
Annotation
              Building on the authors' recent study of tool marks that developed a computer algorithm able to reliably separate matching tool marks from those that do not match, the current report provides additional statistical information that increases the relevance of the measurements obtained.
Abstract
              This was done by first extending the previously developed statistical methodology to allow for self-calibration in controlling rates of false non-matches and then empirically validating the methodology developed by performing experiments that used a different type of tool mark. The authors' previous work focused on the use of the Mann-Whitney U-statistic as an index for assessing the similarity of toolmarks. Although it has been empirically shown to be useful in sorting mark-pairs made by the same tool from mark-pairs made with different tools, it is also influenced by many other aspects of the tool mark structure, such that a single value cannot be used as objective evidence for or against a match.  The current work overcame this difficulty by using multiple test marks made in the laboratory in a "self-calibrated" analysis. Comparison values between lab marks that are known to match form the basis for comparisons between lab marks and evidence marks. This eliminates the need for "universal" critical values (i.e., single sets of constant references value such as those found in commonly used statistical tables) for the comparison index.  A formal statistical analysis based on likelihood functions has been developed to allow for control of false non-match calls. The methodology developed was empirically validated by performing experiments that used a different type of tool mark. Successful validation of the methodology has produced a wide range of possible future applications for the developed statistical algorithm that could revolutionize comparative tool mark analysis. 25 figures, 4 tables, 26 references, and listings in which research findings have been disseminated
      
  
          Additional Details
Grant Number(s)
        2009-DN-R-119


  
  
        
  Agencies
        NIJ-Sponsored


  
  
        
  Publication Type
        Research (Applied/Empirical)
                                Report (Study/Research)
                                Report (Grant Sponsored)
    
  
  
Date Published: August 1, 2013
    
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