Anderson's data Comparison with Spectral Analysis Taxonomic efficiency Conclusion A Comparison with Character Compatibility Analysis. Character compatibility analysis is a technique to reveal patterns of agreement and disagreement among characters in a data matrix. Characters serve as a basis for comparing the taxa in the data matrix.
Characters can have two of more states.
Taxa are considered alike with respect to a character if they share the same character state. Accordingly, a qualitative character is defined as a set of character states, which are mutually exclusive and exhaustive subsets of the collection of terminal taxa in the data matrix. Characters in the latter sense are considered compatible if and only if there is no conflict in membership. If there is a conflict among two characters in the way they subdivide the set of terminal taxa in subsets according to their states, then these characters are considered incompatible. Characters can be tested pairwise as to their compatibility.