方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| 有序逻辑回归（有序 Logit/Probit）× | 逻辑回归× | 多项逻辑回归× | |
|---|---|---|---|
| 领域≠ | 计量经济学 | 研究统计学 | 计量经济学 |
| 方法族≠ | Regression model | Process / pipeline | Regression model |
| 起源年份≠ | 1980 | 1958 | 1974 |
| 提出者≠ | McCullagh (proportional odds / cumulative model) | David Roxbee Cox | McFadden |
| 类型≠ | Cumulative ordinal regression | Method | Multinomial logistic regression |
| 开创性文献≠ | McCullagh, P. (1980). Regression Models for Ordinal Data. Journal of the Royal Statistical Society: Series B, 42(2), 109-142. DOI ↗ | Cox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242. DOI ↗ | McFadden, D. (1974). Conditional Logit Analysis of Qualitative Choice Behavior. In P. Zarembka (Ed.), Frontiers in Econometrics (pp. 105-142). Academic Press. ISBN: 978-0127761503 |
| 别名≠ | ordinal logistic regression, proportional odds model, cumulative logit model, ordered probit | logit model, binomial logistic regression, LR | multinomial logistic regression, polytomous logistic regression, softmax regression, Çok Kategorili Lojistik Regresyon |
| 相关≠ | 4 | 3 | 5 |
| 摘要≠ | Ordered logit is a cumulative regression model for an ordinal dependent variable, fitting a logit (or probit) link to the cumulative category probabilities. Developed in McCullagh's 1980 treatment of regression models for ordinal data, it is the standard tool for Likert-scale, rating, and ranked outcomes. | Logistic regression is a statistical method for modeling the probability of a binary outcome (disease present/absent, success/failure) as a function of continuous and categorical predictors. Developed by David Roxbee Cox (1958), it solves the problem of predicting categorical outcomes by applying a logistic transformation to constrain predictions to the [0,1] probability interval, enabling accurate risk stratification, diagnostic prediction, and causal inference in epidemiology, medicine, and social science. | Multinomial logistic regression is a maximum-likelihood method for a nominal (unordered) dependent variable with more than two categories. Building on McFadden's 1974 treatment of qualitative choice, it gives each category its own set of coefficients relative to a reference category. |
| ScholarGate数据集 ↗ |
|
|
|