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Comparative analysis by independent contrasts (CAIC): an Apple Macintosh application for analysing comparative data
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1995
Year
EngineeringComparative TestApple Macintosh ApplicationGenetic DiversityPhylogeneticsMolecular EcologyBiogeographyMethodology ComparisonBiostatisticsComparative AnalysisAllometric ExponentsStatisticsEvolutionary SignificanceBiodiversityApple MacintoshBiologyNatural SciencesEvolutionary BiologyComparative DataComparative MethodologyContinuous Variables
CAIC is a Macintosh application that enables valid comparative analysis of multi‑species data, addressing the issue that standard regression methods assume independent data points, which is inappropriate for phylogenetically related species. CAIC partitions trait variance into independent contrasts using the species phylogeny, offering separate procedures for continuous and discrete variables, and produces contrasts that can be analyzed in standard statistical software to test correlated evolution, estimate allometric exponents, and compare evolutionary rates. The latest CAIC version is simpler, runs on a broader range of machines, and has been widely adopted, with the software and manual freely downloadable from the authors or anonymous FTP.
CAIC is an application for the Apple Macintosh which allows the valid analysis of comparative (multi-species) data sets that include continuous variables. Comparison among species is the most common technique for testing hypotheses of how organisms are adapted to their environments, but standard statistical tests like regression should not be used with species data. Such tests assume independence of data points, but related species often share traits by common descent rather than through independent adaptation. CAIC uses a phylogeny of the species in the data set to partition the variance among species into independent comparisons (technically, linear contrasts), each comparison being made at a different node in the phylogeny. There are two partitioning procedures--one used when all variables are continuous, the other when one variable is discrete. The resulting comparisons can be analysed validly in standard statistical packages to test hypotheses about correlated evolution among traits, to estimate parameters such as allometric exponents, and to compare rates of evolution. Previous versions of the package have already been used widely; this version is simpler to use and works on a wider range of machines. The package and manual are freely available by anonymous ftp or from the authors.
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