title: Multivariate analysis for animal selection in experimental research.
abstract: BACKGROUND
  Several researchers seek methods for the selection of homogeneous groups of animals in experimental studies, a fact justified because homogeneity is an indispensable prerequisite for casualization of treatments. The lack of robust methods that comply with statistical and biological principles is the reason why researchers use empirical or subjective methods, influencing their results.
  
  
  OBJECTIVE
  To develop a multivariate statistical model for the selection of a homogeneous group of animals for experimental research and to elaborate a computational package to use it.
  
  
  METHODS
  The set of echocardiographic data of 115 male Wistar rats with supravalvular aortic stenosis (AoS) was used as an example of model development. Initially, the data were standardized, and became dimensionless. Then, the variance matrix of the set was submitted to principal components analysis (PCA), aiming at reducing the parametric space and at retaining the relevant variability. That technique established a new Cartesian system into which the animals were allocated, and finally the confidence region (ellipsoid) was built for the profile of the animals' homogeneous responses. The animals located inside the ellipsoid were considered as belonging to the homogeneous batch; those outside the ellipsoid were considered spurious.
  
  
  RESULTS
  The PCA established eight descriptive axes that represented the accumulated variance of the data set in 88.71%. The allocation of the animals in the new system and the construction of the confidence region revealed six spurious animals as compared to the homogeneous batch of 109 animals.
  
  
  CONCLUSIONS
  The biometric criterion presented proved to be effective, because it considers the animal as a whole, analyzing jointly all parameters measured, in addition to having a small discard rate.
authors: Departamento de Bioestatística, Instituto de Ciências Biológicas, Universidade Estadual Paulista, Botucatu, São Paulo, Brazil.
authors: Renan Mercuri
authors: RM
authors: Pinto
authors: Departamento de Clínica Médica, Faculdade de Medicina de Botucatu, Universidade Estadual Paulista, Botucatu, São Paulo, Brazil.
authors: Dijon Henrique Salomé de
authors: DH
authors: Campos
authors: Departamento de Clínica Médica, Faculdade de Medicina de Botucatu, Universidade Estadual Paulista, Botucatu, São Paulo, Brazil.
authors: Loreta Casquel
authors: LC
authors: Tomasi
authors: Departamento de Clínica Médica, Faculdade de Medicina de Botucatu, Universidade Estadual Paulista, Botucatu, São Paulo, Brazil.
authors: Antonio Carlos
authors: AC
authors: Cicogna
authors: Departamento de Clínica Médica, Faculdade de Medicina de Botucatu, Universidade Estadual Paulista, Botucatu, São Paulo, Brazil.
authors: Katashi
authors: K
authors: Okoshi
authors: Departamento de Bioestatística, Instituto de Ciências Biológicas, Universidade Estadual Paulista, Botucatu, São Paulo, Brazil.
authors: Carlos Roberto
authors: CR
authors: Padovani
mesh_terms: D000818:Animals; D021921:Aortic Stenosis, Supravalvular / Q000000981:diagnostic imaging*; D004195:Disease Models, Animal; D008297:Male; D015233:Models, Statistical; D015999:Multivariate Analysis; D017208:Rats, Wistar; D012016:Reference Values; D015203:Reproducibility of Results; D012107:Research Design / Q000592:standards*; D012985:Software Design; D014463:Ultrasonography
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