Regression Models for Binary Dependent Variables Using Stata, SAS, R, LIMDEP, and SPSS


Hun Myoung Park
Fall 2010

Table of Contents (pdf)

  1. Introduction
  2. Binary Logit Regression Model
    • 2.1 Binary Logit Model in Stata (.logit)
    • 2.2 Using SPost Commands in Stata
    • 2.3 Binary Logit Model in SAS: PROC LOGISTIC and PROC PROBIT
    • 2.4 Binary Logit Model in SAS: PROC QLIM and PROC GENMOD
    • 2.5 Binary Logit Model in R
    • 2.6 Binary Logit Model in LIMDEP (Logit$)
    • 2.7 Binary Logit Model in SPSS
  3. Binary Probit Regression Model
    • 3.1 Binary Probit Model in Stata (.probit)
    • 3.2 Binary Probit Model in SAS: PROC LOGISTIC and PROC PROBIT
    • 3.3 Binary Probit Model in SAS: PROC QLIM and PROC GENMOD
    • 3.4 Binary Probit Model in R
    • 3.5 Binary Probit Model in LIMDEP (Probit$)
    • 3.6 Binary Probit Model in SPSS
  4. Bivariate Probit Regression Models
    • 4.1 Bivariate Probit Model in Stata (.biprobit)
    • 4.2 Recursive Bivariate Probit Model in Stata (.biprobit)
    • 4.3 Bivariate Probit Models in SAS: PROC QLIM
    • 4.4 Bivariate Probit Models in LIMDEP (Bivariateprobit$)
  5. Conclusion
  6. References

This document summarizes regression models for categorical dependent variables and illustrates how to estimate individual models using Stata 11, SAS 9.2, R 2.9, LIMDEP 9, and SPSS 17. For logit and probit ordinal and nominal outcome variable models, see Regression Models for Ordinal and Nominal Dependent Variables.

The citation of this document should read: "Park, Hun Myoung. 2009. Regression Models for Binary Dependent Variables Using Stata, SAS, R, LIMDEP, and SPSS. Working Paper. The University Information Technology Services (UITS) Center for Statistical and Mathematical Computing, Indiana University."

Data Sets

   Social Trust (GSS 2000/2002): csv | SAS | SAS script | Stata | Stata script | R script | LIMDEP
   Travel choice (Greene 2003): csv | SAS | Stata (.dta) | LIMDEP