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ポアソン回帰と負の二項回帰×パネルデータ固定効果モデル×
分野計量経済学計量経済学
系統Regression modelRegression model
提唱年19982014
提唱者Cameron & Trivedi (textbook treatment); Hilbe (negative binomial)Hsiao (textbook treatment); within transformation of panel data
種類Generalized linear model for count dataPanel data regression
原典Cameron, A. C. & Trivedi, P. K. (1998). Regression Analysis of Count Data. Cambridge University Press. DOI ↗Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press. DOI ↗
別名count regression, log-linear count model, negative binomial regression, Poisson / Negatif Binom Regresyonfixed effects model, within estimator, panel fixed-effects regression, Panel Veri — Sabit Etkiler Modeli
関連45
概要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.The Panel Data Fixed Effects model estimates relationships from panel data (the same units observed over several time periods) while controlling for unit- and/or time-specific effects, supporting causal inference. It is developed as the within estimator in standard treatments such as Hsiao's Analysis of Panel Data (2014).
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ScholarGate手法を比較: Poisson Regression · Panel Fixed Effects. 2026-06-17に以下より取得 https://scholargate.app/ja/compare