Research Article Comparing covariance matrices: random skewers method compared to the common principal components model
Genet. mol. biol
; 30(2): 461-469, Mar. 2007. tab, ilus, graf
Artigo
em Inglês
| LILACS
| ID: lil-452828
Biblioteca responsável:
BR1.1
ABSTRACT
Comparisons of covariance patterns are becoming more common as interest in the evolution of relationships between traits and in the evolutionary phenotypic diversification of clades have grown. We present parallel analyses of covariance matrix similarity for cranial traits in 14 New World Monkey genera using the Random Skewers (RS), T-statistics, and Common Principal Components (CPC) approaches. We find that the CPC approach is very powerful in that with adequate sample sizes, it can be used to detect significant differences in matrix structure, even between matrices that are virtually identical in their evolutionary properties, as indicated by the RS results. We suggest that in many instances the assumption that population covariance matrices are identical be rejected out of hand. The more interesting and relevant question is, How similar are two covariance matrices with respect to their predicted evolutionary responses? This issue is addressed by the random skewers method described here.
Texto completo:
Disponível
Coleções:
Bases de dados internacionais
Base de dados:
LILACS
Tipo de estudo:
Ensaio clínico controlado
/
Estudo prognóstico
Idioma:
Inglês
Revista:
Genet. mol. biol
Assunto da revista:
Genética
Ano de publicação:
2007
Tipo de documento:
Artigo
/
Documento de projeto
País de afiliação:
Brasil
/
Estados Unidos
Instituição/País de afiliação:
Universidade de São Paulo/BR
/
Washington University School of Medicine/US