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رگرسیون چندمتغیره خطی چندگانه×تحلیل کوواریانس چندمتغیره (MANCOVA)×
حوزهآمارآمار
خانوادهRegression modelHypothesis test
سال پیدایش20071970
پدیدآورJohnson & Wichern (textbook treatment); classical multivariate least squaresExtension of MANOVA and ANCOVA traditions; consolidated in multivariate textbooks by the 1970s–1980s
نوعMultivariate linear regressionParametric multivariate mean comparison with covariate control
منبع بنیادینJohnson, R. A. & Wichern, D. W. (2007). Applied Multivariate Statistical Analysis (6th ed.). Pearson. ISBN: 978-0131877153Tabachnick, B. G. & Fidell, L. S. (2019). Using Multivariate Statistics (7th ed.). Pearson. ISBN: 978-0134790541
نام‌های دیگرmultivariate multiple regression, MLR with multiple dependent variables, multiple-outcome regression, Çok Değişkenli Regresyon (MLR — Çoklu DV)MANCOVA, multivariate ANCOVA, MANOVA with covariates, MANCOVA — Çok Değişkenli Kovaryans Analizi
مرتبط55
خلاصهMultivariate regression is a linear regression method that predicts several continuous dependent variables at the same time from a shared set of predictors. As developed in standard treatments such as Johnson and Wichern's Applied Multivariate Statistical Analysis (2007), each response equation can be fitted by ordinary least squares while the covariance structure of the residuals is used for joint testing across outcomes.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).
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ScholarGateمقایسهٔ روش‌ها: Multivariate Regression · MANCOVA. بازیابی‌شده در 2026-06-15 از https://scholargate.app/fa/compare