Journal Article10.1177/0049124109346162
A Conceptual Framework for Ordered Logistic Regression Models
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TL;DR: In this article, the authors identify 12 distinct models that rely on logistic regression and fit within a framework of three major approaches with variations within each approach based on the application of the proportional odds assumption.
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Abstract: Ordinal-level measures are very common in social science research. Researchers often analyze ordinal dependent variables using the proportional odds logistic regression model. However, this ‘‘traditional’’ method is one of many different types of logistic regression models available for the analysis of ordered response variables. In this article, the author identifies 12 distinct models that rely on logistic regression and fit within a framework of three major approaches with variations within each approach based on the application of the proportional odds assumption. This typology provides a degree of conceptual clarity that is missing in the extant literature on logistic regression models for ordinal outcomes. The author illustrates the similarities and differences among the different models with examples from the General Social Survey and the American National Election Study.
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References
Regression Models and Life-Tables
TL;DR: The analysis of censored failure times is considered in this paper, where the hazard function is taken to be a function of the explanatory variables and unknown regression coefficients multiplied by an arbitrary and unknown function of time.
28.6K
•Book
Limited-Dependent and Qualitative Variables in Econometrics
G. S. Maddala
- 01 Jan 1983
TL;DR: In this article, the authors present a survey of the use of truncated distributions in the context of unions and wages, and some results on truncated distribution Bibliography Index and references therein.
15.5K
Generalized Linear Models
John A. Nelder,R. W. M. Wedderburn +1 more
- 01 May 1972
TL;DR: In this paper, the authors used iterative weighted linear regression to obtain maximum likelihood estimates of the parameters with observations distributed according to some exponential family and systematic effects that can be made linear by a suitable transformation.
9.7K
•Book
Regression Models for Categorical and Limited Dependent Variables
J. Scott Long
- 09 Jan 1997
TL;DR: In this article, the authors propose Continuous Outcomes Binary Outcomes Testing and Fit Ordinal Outcomes Numeric Outcomes and Numeric Numeric Count Outcomes (NOCO).
7.5K