Regression Models for Ordinal and Nominal Dependent Variables Using SAS, Stata, LIMDEP, and SPSS
Fall 2009
Table of Contents (pdf)
- Introduction
- Ordered Logit and Probit Regression Models
- 2.1 Ordered Logit Model in Stata (.ologit)
- 2.2 Ordered Probit Model in Stata (.oprobit)
- 2.3 Parallel Regression Assumption and the Generalized Ordered Logit Model
- 2.4 Ordered Logit Model in SAS
- 2.5 Ordered Probit Model in SAS
- 2.6 Ordered Logit and Probit Models in LIMDEP (Ordered$)
- 2.7 Ordered Logit and Probit Models in SPSS
- Multinomial Logit Regression Model
- 3.1 Multinomial Logit and Probit Models in Stata (.mlogit and .mprobit)
- 3.2 Interpretation of the Multinomial Logit Model in Stata
- 3.3 Multinomial Logit Model in SAS: PROC LOGISTIC and PROC CATMOD
- 3.4 Multinomial Logit Model in LIMDEP (Mlogit$)
- 3.5 Multinomial Logit Model in SPSS
- Conditional Logit Regression Model
- 4.1 Conditional Logit Model in Stata (.clogit)
- 4.2 Conditional Logit Model in SAS: PROC MDC
- 4.3 Conditional Logit Model in LIMDEP (Clogit$)
- 4.4 Conditional Logit Model in SPSS
- Nested Logit Regression Model
- 5.1 Nested Logit Model in Stata (.nlogit)
- 5.2 Nested Logit Model in SAS: PROC MDC
- Conclusion
- References
This document summarizes regression models for ordinal and nomial response variables and illustrates how to estimate
individual models using SAS 9.2, Stata 11, LIMDEP 9, and SPSS 17. For logit and probit regression models for
binary outcome variables, see Regression Models for Binary Dependent Variables.
The citation of this document should read: "Park, Hun Myoung. 2009. Regression Models for Ordinal and Nominal Dependent Variables Using SAS, Stata, LIMDEP, and SPSS. Working Paper.
The University Information Technology Services (UITS) Center for Statistical and Mathematical Computing, Indiana University."
Data Sets
Religious intensity (GSS 2000 and 2002): csv | SAS | Stata (.dta) | Stata script (.do) | LIMDEP (.lpj)Travel choice (Greene 2003): csv | SAS | Stata (.dta) | LIMDEP (.lpj)
