Comparar métodos

	Regressão Logística Ordinal (Modelo de Odds Proporcionais)	Regressão por Mínimos Quadrados Ordinários (MQO)
Área	Estatística	Econometria
Família	Regression model	Regression model
Ano de origem	2010	2019
Autor original	Agresti (textbook treatment); proportional odds model	Wooldridge (textbook treatment); classical least squares
Tipo	Ordinal logistic regression	Linear regression
Fonte seminal	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
Outros nomes	proportional odds model, ordered logit, ordinal logistic regression, Ordinal Regresyon (Proportional Odds)	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Relacionados	5	5
Resumo	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).