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Hurdle-model for tælledata×Logistisk regression×
FagområdeStatistikForskningsstatistik
FamilieRegression modelProcess / pipeline
Oprindelsesår19861958
OphavspersonMullahyDavid Roxbee Cox
TypeTwo-part count modelMethod
Oprindelig kildeMullahy, J. (1986). Specification and Testing of Some Modified Count Data Models. Journal of Econometrics, 33(3), 341–365. DOI ↗Cox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242. DOI ↗
Aliasserhurdle count model, two-part count model, zero-truncated count model, Engel Modeli (Hurdle Model)logit model, binomial logistic regression, LR
Relaterede53
ResuméThe 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.
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ScholarGateSammenlign metoder: Hurdle Model · Logistic Regression. Hentet 2026-06-17 fra https://scholargate.app/da/compare