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تحلیل داده‌های پانل غیرخطی×رگرسیون لجستیک×
حوزهاقتصادسنجیآمار پژوهش
خانوادهRegression modelProcess / pipeline
سال پیدایش1986–20101958
پدیدآورCheng Hsiao; Jeffrey M. WooldridgeDavid Roxbee Cox
نوعPanel data model (nonlinear)Method
منبع بنیادینWooldridge, 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 ↗
نام‌های دیگرnonlinear panel models, panel nonlinear econometrics, fixed-effects nonlinear models, random-effects nonlinear modelslogit model, binomial logistic regression, LR
مرتبط43
خلاصهNonlinear 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.
ScholarGateمجموعه‌داده
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ScholarGateمقایسهٔ روش‌ها: Nonlinear Panel Data Analysis · Logistic Regression. بازیابی‌شده در 2026-06-15 از https://scholargate.app/fa/compare