Comparar métodos

	Análise de Covariância (ANCOVA)	Teste H de Kruskal-Wallis	Análise Multivariada de Covariância (MANCOVA)
Área	Estatística	Estatística	Estatística
Família	Hypothesis test	Hypothesis test	Hypothesis test
Ano de origem	1932	1952	1970
Autor original	Ronald A. Fisher	William Kruskal & W. Allen Wallis	Extension of MANOVA and ANCOVA traditions; consolidated in multivariate textbooks by the 1970s–1980s
Tipo	Parametric group comparison with covariate control	Nonparametric group comparison	Parametric multivariate mean comparison with covariate control
Fonte seminal	Tabachnick, B.G. & Fidell, L.S. (2013). Using Multivariate Statistics (6th ed.). Pearson. ISBN: 978-0205849574	Kruskal, W. H. & Wallis, W. A. (1952). Use of ranks in one-criterion variance analysis. Journal of the American Statistical Association, 47(260), 583–621.	Tabachnick, B. G. & Fidell, L. S. (2019). Using Multivariate Statistics (7th ed.). Pearson. ISBN: 978-0134790541
Outros nomes	analysis of covariance, covariance analysis, ANCOVA (Kovaryans Analizi)	Kruskal-Wallis H test, one-way ANOVA on ranks, Kruskal-Wallis one-way analysis of variance, Kruskal-Wallis Testi	MANCOVA, multivariate ANCOVA, MANOVA with covariates, MANCOVA — Çok Değişkenli Kovaryans Analizi
Relacionados	4	5	5
Resumo	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).	The Kruskal-Wallis H test is a nonparametric hypothesis test that compares three or more independent groups to decide whether their distributions (typically their medians) differ. Introduced by William Kruskal and W. Allen Wallis in 1952, it works on ranks rather than raw values and is the distribution-free counterpart to one-way ANOVA.	MANCOVA (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).