Σύγκριση μεθόδων

	Μοντέλο Κατωφλίου για Δεδομένα Καταμέτρησης	Λογιστική Παλινδρόμηση
Πεδίο	Στατιστική	Ερευνητική Στατιστική
Οικογένεια	Regression model	Process / pipeline
Έτος προέλευσης	1986	1958
Δημιουργός	Mullahy	David Roxbee Cox
Τύπος	Two-part count model	Method
Θεμελιώδης πηγή	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.
Εναλλακτικές ονομασίες	hurdle count model, two-part count model, zero-truncated count model, Engel Modeli (Hurdle Model)	logit model, binomial logistic regression, LR
Συναφείς	5	3
Σύνοψη	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.