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رگرسیون لجستیک×تحلیل کوواریانس چندمتغیره (MANCOVA)×
حوزهآمار پژوهشآمار
خانوادهProcess / pipelineHypothesis test
سال پیدایش19581970
پدیدآورDavid Roxbee CoxExtension of MANOVA and ANCOVA traditions; consolidated in multivariate textbooks by the 1970s–1980s
نوعMethodParametric multivariate mean comparison with covariate control
منبع بنیادینCox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242. DOI ↗Tabachnick, B. G. & Fidell, L. S. (2019). Using Multivariate Statistics (7th ed.). Pearson. ISBN: 978-0134790541
نام‌های دیگرlogit model, binomial logistic regression, LRMANCOVA, multivariate ANCOVA, MANOVA with covariates, MANCOVA — Çok Değişkenli Kovaryans Analizi
مرتبط35
خلاصهLogistic regression is a statistical method for modeling the probability of a binary outcome (disease present/absent, success/failure) as a function of continuous and categorical predictors. Developed by David Roxbee Cox (1958), it solves the problem of predicting categorical outcomes by applying a logistic transformation to constrain predictions to the [0,1] probability interval, enabling accurate risk stratification, diagnostic prediction, and causal inference in epidemiology, medicine, and social science.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: Logistic Regression · MANCOVA. بازیابی‌شده در 2026-06-18 از https://scholargate.app/fa/compare