- News about the sampleSelection project are available at the project's R-Forge site.

**censReg**: censored regression ("Tobit") models**intReg**: interval regression models**mvProbit**: multivariate probit models**sampleSelection**: sample selection ("Heckman") models

**censReg**: http://cran.r-project.org/package=censReg**intReg**: http://cran.r-project.org/package=intReg**mvProbit**: http://cran.r-project.org/package=mvProbit**sampleSelection**: http://cran.r-project.org/package=sampleSelection

install.packages( "packageName" )

install.packages( "packageName", repos="http://R-Forge.R-project.org" )

- All packages in the "sampleSelection" project are published under the GNU General Public License (GPL)

**Can the sampleSelection package estimate selection models, where the second stage is binary?**

The latest versions of the sampleSelection package (>= 0.7) can estimate models, where the second stage is binary.

Thilo Klein informed us that this model can be also estimated by the`vglm`function and the`constraints`option in the VGAM package:Selection: C = 1 if Xa + U > 0; else C = 0 Outcome: Y = 1 if Zb + V > 0; else Y = 0 const <- list() const$"(Intercept)" <- diag(3) const$x <- as.matrix(c(1,0,0)) const$z <- as.matrix(c(0,1,0)) const$C <- as.matrix(c(0,1,0)) fit <- vglm(cbind(C, y) ~ x + z + C, binom2.rho(zero=3),control=vglm.control(maxit=maxit),constraints=const) constraints(fit)

Furthermore, he made us aware of that the`SemiParBIVProbit`function in the SemiParBIVProbit package also can estimate such models.

Last Update: 11 June 2014