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Análise Multivariada de Covariância (MANCOVA)×Análise de Covariância (ANCOVA)×
ÁreaEstatísticaEstatística
FamíliaHypothesis testHypothesis test
Ano de origem19701932
Autor originalExtension of MANOVA and ANCOVA traditions; consolidated in multivariate textbooks by the 1970s–1980sRonald A. Fisher
TipoParametric multivariate mean comparison with covariate controlParametric group comparison with covariate control
Fonte seminalTabachnick, B. G. & Fidell, L. S. (2019). Using Multivariate Statistics (7th ed.). Pearson. ISBN: 978-0134790541Tabachnick, B.G. & Fidell, L.S. (2013). Using Multivariate Statistics (6th ed.). Pearson. ISBN: 978-0205849574
Outros nomesMANCOVA, multivariate ANCOVA, MANOVA with covariates, MANCOVA — Çok Değişkenli Kovaryans Analizianalysis of covariance, covariance analysis, ANCOVA (Kovaryans Analizi)
Relacionados54
ResumoMANCOVA (Multivariate Analysis of Covariance) is a parametric hypothesis test that simultaneously compares two or more groups on multiple continuous dependent variables while statistically controlling for one or more covariates. It extends MANOVA by incorporating covariate adjustment, a tradition consolidated in multivariate statistical methodology by the 1970s and authoritatively documented by Tabachnick and Fidell (2019).ANCOVA is a parametric hypothesis test that compares the adjusted means of two or more independent groups while statistically controlling for one or more continuous covariates. By removing the portion of outcome variance explained by the covariate, ANCOVA increases statistical precision and produces fairer group comparisons. The method builds on the general linear model framework consolidated by Fisher in the early 1930s and is described comprehensively by Tabachnick and Fidell (2013).
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ScholarGateComparar métodos: MANCOVA · ANCOVA. Recuperado em 2026-06-18 de https://scholargate.app/pt/compare