विधियों की तुलना करें

	गणना डेटा के लिए हर्डल मॉडल	लॉजिस्टिक रिग्रेशन
क्षेत्र	सांख्यिकी	अनुसंधान सांख्यिकी
परिवार	Regression model	Process / pipeline
उद्भव वर्ष	1986	1958
प्रवर्तक	Mullahy	David Roxbee Cox
प्रकार	Two-part count model	Method
मौलिक स्रोत	Mullahy, J. (1986). Specification and Testing of Some Modified Count Data Models. Journal of Econometrics, 33(3), 341–365.	Cox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242.
उपनाम	hurdle count model, two-part count model, zero-truncated count model, Engel Modeli (Hurdle Model)	logit model, binomial logistic regression, LR
संबंधित	5	3
सारांश	The hurdle model is a two-part count-data model introduced by Mullahy (1986). A first stage models the binary choice of crossing a hurdle (a zero versus a non-zero count), and a second stage models the strictly positive counts with a zero-truncated distribution such as a zero-truncated Poisson or negative binomial.	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.