ScholarGate
Asistent

Porovnat metody

Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.

Logistická regrese×Mnohonásobná regresní analýza×
OborStatistika ve výzkumuStatistika ve výzkumu
RodinaProcess / pipelineProcess / pipeline
Rok vzniku19581801
TvůrceDavid Roxbee CoxCarl Friedrich Gauss
TypMethodMethod
Původní zdrojCox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242. DOI ↗Draper, N. R., & Smith, H. (1966). Applied Regression Analysis. John Wiley & Sons. link ↗
Další názvylogit model, binomial logistic regression, LRMLR, multivariate regression, linear regression
Příbuzné34
ShrnutíLogistic 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.Multiple regression analysis is a statistical method for modeling the relationship between a continuous dependent variable and two or more independent variables (predictors). Originating from Gauss's early 19th-century work and formalized by Draper and Smith (1966), it estimates linear equations predicting outcomes from multiple predictors while accounting for confounding relationships, making it indispensable in epidemiology, economics, psychology, and clinical research.
ScholarGateDatová sada
  1. v1
  2. 2 Zdroje
  3. PUBLISHED
  1. v1
  2. 3 Zdroje
  3. PUBLISHED

Přejít na hledání Stáhnout prezentaci

ScholarGatePorovnat metody: Logistic Regression · Multiple Regression Analysis. Získáno 2026-06-15 z https://scholargate.app/cs/compare