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
modifies their code.

Recursive Two-Stage Models to Address Endogeneity
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>.

person(given = "Andrew J.", family = "Spieker", role = c("aut", "cre"), email = "aspieker@upenn.edu")
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.

endorse: R Package for Analyzing Endorsement Experiments
Yuki Shiraito <shiraito@princeton.edu>, Kosuke Imai
<kimai@princeton.edu>
This R package implements the statistical model proposed
by Bullock, Imai, and Shapiro (2011; Political Analysis) to
analyze endorsement experiments.  Endorsement experiments are a
survey methodology for eliciting truthful responses to
sensitive questions.  This methodology is helpful when
measuring support for socially sensitive political actors such
as militant groups.  The model is fitted with the Markov chain
Monte Carlo algorithm and produces the output containing draws
from the posterior distribution.