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Regresi Poisson dan Binomial Negatif×Model Kesan Tetap Data Panel×
BidangEkonometrikEkonometrik
KeluargaRegression modelRegression model
Tahun asal19982014
PengasasCameron & Trivedi (textbook treatment); Hilbe (negative binomial)Hsiao (textbook treatment); within transformation of panel data
JenisGeneralized linear model for count dataPanel data regression
Sumber perintisCameron, 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 ↗
Aliascount 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
Berkaitan45
RingkasanPoisson 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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ScholarGateBandingkan kaedah: Poisson Regression · Panel Fixed Effects. Dicapai 2026-06-17 daripada https://scholargate.app/ms/compare