השוואת שיטות

	רגרסיית בינום שלילי	רגרסיה לוגיסטית
תחום	אקונומטריקה	סטטיסטיקה למחקר
משפחה	Regression model	Process / pipeline
שנת המקור	2011	1958
הוגה השיטה	Hilbe (textbook treatment); generalized linear model framework	David Roxbee Cox
סוג	Generalized linear model for count data	Method
מקור מכונן	Hilbe, J. M. (2011). Negative Binomial Regression (2nd ed.). Cambridge University Press.	Cox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242.
כינויים	NB regression, NB2 regression, negatif binom regresyonu	logit model, binomial logistic regression, LR
קשורות	4	3
תקציר	Negative Binomial Regression is a generalized linear model for count outcomes that extends Poisson regression to handle overdispersion, where the variance of the counts exceeds their mean. Developed in the GLM tradition and treated in depth by Hilbe (2011), it adds a dispersion parameter so that inference stays valid when Poisson would understate the spread of the data.	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.