手法を比較

	順序ロジスティック回帰（比例オッズモデル）	最小二乗法 (OLS) 回帰
分野	統計学	計量経済学
系統	Regression model	Regression model
提唱年	2010	2019
提唱者	Agresti (textbook treatment); proportional odds model	Wooldridge (textbook treatment); classical least squares
種類	Ordinal logistic regression	Linear regression
原典	Agresti, A. (2010). Analysis of Ordinal Categorical Data (2nd ed.). Wiley.	Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
別名	proportional odds model, ordered logit, ordinal logistic regression, Ordinal Regresyon (Proportional Odds)	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
関連	5	5
概要	Ordinal logistic regression models an ordered categorical outcome — such as a Likert rating, a satisfaction level, or an education tier — as a function of predictors. It is the ordinal extension of logistic regression, developed in standard treatments such as Agresti's Analysis of Ordinal Categorical Data (2010), and in its most common form it is the proportional odds model.	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).