Title: Easily Encrypt and Decrypt Data Frame/Tibble Columns or Files
Packaged: 2019-04-25 06:54:01 UTC; eharrison

Title: Endogenous Switching Regression Models
person(given = "Seong", family = "Yun", role = "aut"),
person(given = "Benjamin", family = "Gramig", role = "aut"))
Description: Maximum likelihood estimation of endogenous switching regression models from Heckman (1979) <doi:10.2307/1912352> and estimation of treatment effects.

Title: R Package for Fitting Multinomial Probit Models with Endogenous
Author: Lane F. Burgette <burgette@stat.wisc.edu>
Maintainer: Lane F. Burgette <burgette@stat.wisc.edu>
Description: endogMNP is an R package that fits the Bayesian
multinomial probit model with endogenous selection, which is
sometimes called an endogenous switching model.  This can be
used to model discrete choice data when respondents select
themselves into one of several outcomes.  This package is based
on the MNP package by Kosuke Imai and David A. van Dyk.  This
Packaged: Sat Jun 20 17:43:12 2009; lburgette

Author: Lane F. Burgette <lb131@stat.duke.edu>
Maintainer: Lane F. Burgette <lb131@stat.duke.edu>
Description: endogMNP is an R package that fits a Bayesian multinomial
probit model with endogenous selection, which is sometimes
called an endogenous switching model.  This can be used to
model discrete choice data when respondents select themselves
into one of several groups.  This package is based on the MNP
package by Kosuke Imai and David A. van Dyk.  This package
Packaged: 2009-08-27 20:13:38 UTC; lburgette

Packaged: 2010-03-31 04:41:04 UTC; lburgette

Title: Recursive Two-Stage Models to Address Endogeneity
Description: Various recursive two-stage models to address the endogeneity issue of treatment variables in observational study or mediators in experiments. The details of the models are discussed in Peng (2022) <doi:10.2139/ssrn.3494856>.
Imports: pbivnorm, maxLik, statmod, MASS

Title: Classical Simultaneous Equation Models
Maintainer: Andrew J. Spieker <aspieker@upenn.edu>
Authors@R: person(given = "Andrew J.", family = "Spieker", role = c("aut", "cre"), email = "aspieker@upenn.edu")
Description: Likelihood-based approaches to estimate linear regression parameters and treatment effects in the presence of endogeneity. Specifically, this package includes James Heckman's classical simultaneous equation models-the sample selection model for outcome selection bias and hybrid model with structural shift for endogenous treatment. For more information, see the seminal paper of Heckman (1978) <DOI:10.3386/w0177> in which the details of these models are provided. This package accommodates repeated measures on subjects with a working independence approach. The hybrid model further accommodates treatment effect modification.