Compară metode

	Regresie logistică ordinală	Regresia prin metoda celor mai mici pătrate ordinare (OLS)
Domeniu	Statistică	Econometrie
Familie	Regression model	Regression model
Anul apariției	1980	2019
Autorul original	Peter McCullagh	Wooldridge (textbook treatment); classical least squares
Tip	Ordinal regression / GLM	Linear regression
Sursa seminală	McCullagh, P. (1980). Regression models for ordinal data. Journal of the Royal Statistical Society: Series B (Methodological), 42(2), 109–142.	Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
Denumiri alternative	proportional-odds model, cumulative link model, ordered logit, OLR	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Înrudite	6	5
Rezumat	Ordinal logistic regression — most commonly the proportional-odds model — estimates the relationship between one or more predictors and an ordered categorical outcome (e.g., Likert scales, disease severity grades, educational attainment levels). It models cumulative log-odds across the ordered categories while assuming a single shared effect of each predictor at all thresholds.	Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE).