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Ordinal Logistic Regression (Proportional Odds Model)×Methode der kleinsten Quadrate (OLS)×
FachgebietStatistikÖkonometrie
FamilieRegression modelRegression model
Entstehungsjahr20102019
UrheberAgresti (textbook treatment); proportional odds modelWooldridge (textbook treatment); classical least squares
TypOrdinal logistic regressionLinear regression
Wegweisende QuelleAgresti, A. (2010). Analysis of Ordinal Categorical Data (2nd ed.). Wiley. DOI ↗Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
Aliasnamenproportional odds model, ordered logit, ordinal logistic regression, Ordinal Regresyon (Proportional Odds)ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Verwandt55
ZusammenfassungOrdinal 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).
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ScholarGateMethoden vergleichen: Ordinal Regression · OLS Regression. Abgerufen am 2026-06-17 von https://scholargate.app/de/compare