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| Logistic Regression× | Multivariate Kovariancia-elemzés (MANCOVA)× | |
|---|---|---|
| Tudományterület≠ | Kutatási statisztika | Statisztika |
| Módszercsalád≠ | Process / pipeline | Hypothesis test |
| Keletkezés éve≠ | 1958 | 1970 |
| Megalkotó≠ | David Roxbee Cox | Extension of MANOVA and ANCOVA traditions; consolidated in multivariate textbooks by the 1970s–1980s |
| Típus≠ | Method | Parametric multivariate mean comparison with covariate control |
| Alapmű≠ | Cox, 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 |
| Alternatív nevek≠ | logit model, binomial logistic regression, LR | MANCOVA, multivariate ANCOVA, MANOVA with covariates, MANCOVA — Çok Değişkenli Kovaryans Analizi |
| Kapcsolódó≠ | 3 | 5 |
| Összefoglaló≠ | Logistic 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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