Logistic Regression Models for Ordinal Response Variables

By A. O’Connell. 2005

620 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/1e88d5641c42b9c6e40535099802fbcd9e8d4c9d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Management Science and Operations Research

1. K. Andereck
2. J. Gómez
3. Simon Liu
4. Cherng-Jyh Yen
5. Jack H. Noone
6. Alex Y. Lo
7. C. Stephens
8. Chi-Yung Jim

In Statistics and Probability

1. K. Andereck
2. J. Gómez
3. Simon Liu
4. Cherng-Jyh Yen
5. Jack H. Noone
6. Alex Y. Lo
7. C. Stephens
8. Chi-Yung Jim

Citations in the corpus

• Protest response and willingness to pay for culturally significant urban trees: Implications for Contingent Valuation Method (2015, methodology): “Ordered regression analyses were used to examine the survey data (Agresti and Finlay, 1997; O'Connell, 2006).”
• Community College Online Course Retention and Final Grade: Predictability of Social Presence. (2009, methodology): “Then, an ordinal logistic regression analysis (O’Connell, 2006) was conducted to examine the predictive relationship between social presence, and the ordinal criterion variable, final grade.”
• Ordinal Regression Analysis: Fitting the Proportional Odds Model Using Stata, SAS and SPSS (2009, positive): “…model (Agresti, 1996, 2002; Armstrong & Sloan, 1989; Long, 1997, Long & Freese, 2006; McCullagh, 1980; McCullagh & Nelder, 1989; Powers & Xie, 2000; O'Connell, 2006), is a commonly used model for the analysis of ordinal categorical data and comes from the class of generalized linear models.”
• Preretirement Planning and Well-Being in Later Life (2009, methodology): “The estimated coefficient was then used to calculate the odds ratio (OR; see Chan 2005; Norusis 2006; O’Connell 2006).”
• Ordinal Regression Analysis: Using Generalized Ordinal Logistic Regression Models to Estimate Educational Data (2012, positive): “The assumption of proportional odds is often violated, however, because it is strongly affected by sample size and the number of covariate patterns – for example, including continuous covariates or interactions as the predictors (Allison, 1999; Brant, 1990; O'Connell, 2006).”
• Exploring the Nature of Tourism and Quality of Life Perceptions among Residents (2011, methodology): “It is the best tool for estimating a set of regression coefficients that predict the probability of the outcome of interest that is measured on an ordinal scale (O’Connell 2006).”