Premium
Classification systems for discrete variables used in forensic anthropology
Author(s) -
Finnegan Michael,
McGuire Stephen A.
Publication year - 1979
Publication title -
american journal of physical anthropology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.146
H-Index - 119
eISSN - 1096-8644
pISSN - 0002-9483
DOI - 10.1002/ajpa.1330510406
Subject(s) - crania , pairwise comparison , computer science , metric (unit) , linear discriminant analysis , machine learning , artificial intelligence , mathematics , data mining , geography , engineering , archaeology , operations management
In recent years a number of papers have been presented on the usefulness of non‐metric traits of the cranial and infracranial skeleton in order that one, some few, or a subsample of crania may be allocated to a pair, family, or larger group. These papers have explored (1) which traits should be used, (2) the theoretical implications of assignment, and (3) the methodology for making these assignments. This paper addresses itself to the theoretical implications of assignment and the methodology for making these assignments. Classification techniques based on the Bayes' theorem, weight of evidence procedures, linear discriminant functions, tally method and the Rubison procedure, were utilized in the first level of analysis. The result suggests that methodologies used must contain an accommodation for correlation between bilateral traits and that pairwise classification procedures are often more applicable than multiple classification procedures considering a large number of groups. The accuracy of various methods starts at slightly better than 50%, while the better methods produce results above the 90% level. Results further show that when acceptable assignments are made the theoretical implications of these assignments do not necessarily suggest the use of a particular methodology, and for ease of analysis the simplest methodology should be used.