Why does a method that fails continue to be used? The answer

Alan R. Templeton

Research output: Contribution to journalComment/Debate

Abstract

It has been claimed that hundreds of researchers use nested clade phylogeographic analysis (NCPA) based on what the method promises rather than requiring objective validation of the method. The supposed failure of NCPA is based upon the argument that validating it by using positive controls ignored type I error, and that computer simulations have shown a high type I error. The first argument is factually incorrect: the previously published validation analysis fully accounted for both type I and type II errors. The simulations that indicate a 75% type I error rate have serious flaws and only evaluate outdated versions of NCPA. These outdated type I error rates fall precipitously when the 2003 version of single-locus NCPA is used or when the 2002 multilocus version of NCPA is used. It is shown that the tree-wise type I errors in single-locus NCPA can be corrected to the desired nominal level by a simple statistical procedure, and that multilocus NCPA reconstructs a simulated scenario used to discredit NCPA with 100% accuracy. Hence, NCPA is a not a failed method at all, but rather has been validated both by actual data and by simulated data in a manner that satisfies the published criteria given by its critics. The critics have come to different conclusions because they have focused on the pre-2002 versions of NCPA and have failed to take into account the extensive developments in NCPA since 2002. Hence, researchers can choose to use NCPA based upon objective critical validation that shows that NCPA delivers what it promises.

Original languageEnglish
Pages (from-to)807-812
Number of pages6
JournalEvolution
Volume63
Issue number4
DOIs
StatePublished - Apr 2009
Externally publishedYes

Keywords

  • Computer simulation
  • Nested-clade analysis
  • Phylogeography
  • Statistics

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Genetics
  • General Agricultural and Biological Sciences

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