DOI: 10.5061/dryad.qg91m
title: Data from: Principal component analysis as an alternative treatment for morphometric characters: phylogeny of caseids as a case study

description: In a recent study, the phylogeny of Caseidae (a herbivorous family of
 Palaeozoic synapsids belonging to the paraphyletic grade known as
 pelycosaurs) was analysed with a dataset employing more than three hundred
 continuous morphological characters in an effort to follow the principles
 of total evidence. Continuous characters are a source of great debate,
 with disagreements surrounding their suitability for and treatment in
 phylogenetic analysis. A number of shortcomings were identified in the
 handling of continuous characters in this study of caseids, including the
 use of gap weighting to discretize the characters and potential issues
 with redundancy and character non-independence. Therefore, an alternative
 treatment for these characters is suggested here. First, rather than using
 gap weighting, the continuous characters were analysed in the program TNT,
 in which the raw values can be treated as continuous rather than discrete.
 Second, prior to the phylogenetic analysis, the continuous characters were
 subjected to a log-ratio principal component analysis, and then the
 principal components were included in the character matrix rather than the
 raw ratios. Analysing the original data in TNT produced little difference
 in the results, but using the principal components as continuous
 characters resulted in alternative positions for Caseopsis agilis,
 Ennatosaurus tecton and Caseoides sanangeloensis. The differences are
 judged to be due to the reduced redundancy of the characters, the smaller
 number of principal components not overwhelming the discrete characters
 and the use of a scaling method which allows principal components with a
 higher variance to have a greater influence on the analysis. The positions
 of highly fragmentary fossils depended heavily on the method used to treat
 the missing characters in the principal component analysis, and so the
 method proposed here is not recommended for analysing very incomplete
 taxa.
description: Data 1 - R&N TNT
 fileTNT file used in
 analysis of original data of R&NData
 1.tntData 2 - BPCA PC
 scoresPrincipal component
 scores found using BPCAData
 2.csvData 3 - Iterative
 Imputation PC scoresPrincipal component
 scores identified using iterative imputationData
 3.csvData 4 - BPCA
 loadingsLoadings on each
 morphometric character identified using BPCAData
 4.csvData 5 - Iterative
 Imputation loadingsLoadings on each
 morphometric character identified by iterative
 imputationData
 5.csvData 6 - BPCA TNT
 fileTNT file used in
 analysis of PC characters identified using BPCAData
 6.tntData 7 - Iterative
 Imputation TNT fileTNT file used in the
 analysis of the PC characters identified using Iterative
 ImputationData
 7.tntData 8 - PC character
 loadingsTop 25 most heavily
 loaded characters on the top three principal componentsData
 8.docxData 8The top 25 most highly
 loaded morphometric characters for the first three principal components,
 identified using both methods of treating missing data. The loading is
 shown after the character description