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Nelineárna analýza panelových dát×Logistická regresia×
OdborEkonometriaŠtatistika vo výskume
RodinaRegression modelProcess / pipeline
Rok vzniku1986–20101958
TvorcaCheng Hsiao; Jeffrey M. WooldridgeDavid Roxbee Cox
TypPanel data model (nonlinear)Method
Pôvodný zdrojWooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586Cox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242. DOI ↗
Ďalšie názvynonlinear panel models, panel nonlinear econometrics, fixed-effects nonlinear models, random-effects nonlinear modelslogit model, binomial logistic regression, LR
Príbuzné43
ZhrnutieNonlinear panel data analysis applies nonlinear models — such as probit, logit, Poisson, or Tobit — to repeated observations on the same units over time. It accounts for unit-specific unobserved heterogeneity while capturing non-linear relationships between predictors and the outcome, making it essential when the dependent variable is binary, count-based, censored, or otherwise non-continuous.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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ScholarGatePorovnať metódy: Nonlinear Panel Data Analysis · Logistic Regression. Získané 2026-06-17 z https://scholargate.app/sk/compare