手法を比較

	カウントデータのためのハードルモデル	ポアソン回帰と負の二項回帰
分野	統計学	計量経済学
系統	Regression model	Regression model
提唱年	1986	1998
提唱者	Mullahy	Cameron & Trivedi (textbook treatment); Hilbe (negative binomial)
種類	Two-part count model	Generalized linear model for count data
原典	Mullahy, J. (1986). Specification and Testing of Some Modified Count Data Models. Journal of Econometrics, 33(3), 341–365.	Cameron, A. C. & Trivedi, P. K. (1998). Regression Analysis of Count Data. Cambridge University Press.
別名	hurdle count model, two-part count model, zero-truncated count model, Engel Modeli (Hurdle Model)	count regression, log-linear count model, negative binomial regression, Poisson / Negatif Binom Regresyon
関連	5	4
概要	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.	Poisson regression is a generalized linear model for count outcomes — events tallied as non-negative integers such as hospital admissions, accidents, or article counts. It models the log of the expected count as a linear function of the predictors, and is developed in the standard count-data treatment of Cameron and Trivedi (1998); when the counts are over-dispersed, the closely related negative binomial model (Hilbe, 2011) is preferred.