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Regresi Logistik Ordinal (Model Kebarangkalian Bertindih)×Regresi Kuasa Dua Terkecil Biasa (OLS)×
BidangStatistikEkonometrik
KeluargaRegression modelRegression model
Tahun asal20102019
PengasasAgresti (textbook treatment); proportional odds modelWooldridge (textbook treatment); classical least squares
JenisOrdinal logistic regressionLinear regression
Sumber perintisAgresti, 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
Aliasproportional odds model, ordered logit, ordinal logistic regression, Ordinal Regresyon (Proportional Odds)ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Berkaitan55
RingkasanOrdinal 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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ScholarGateBandingkan kaedah: Ordinal Regression · OLS Regression. Dicapai 2026-06-17 daripada https://scholargate.app/ms/compare