This package contains functions for carrying out instrumental variable estimation of causal effects and power analyses for instrumental variable studies.

Fit the instrumental panel data models: the fixed effects, random
effects and between models.

ivprobit fit an Instrumental variables probit model using the
generalized least squares estimator

Compute the instrumental variables probit model using  the Amemiya's Generalized Least Squares estimators (Amemiya, Takeshi, (1978) <doi: 10.2307/1911443>).

Two-Stage Least-Squares Regression with Diagnostics
c(person(given = "John", family = "Fox", role = c("aut", "cre"), email = "jfox@mcmaster.ca", comment = c(ORCHID = "0000-0002-1196-8012")),
person(given = "Christian", family = "Kleiber", role = "aut", email = "Christian.Kleiber@unibas.ch", comment = c(ORCID = "0000-0002-6781-4733")),
person(given = "Achim", family = "Zeileis", role = "aut", email = "Achim.Zeileis@R-project.org", comment = c(ORCID = "0000-0003-0918-3766")))
Instrumental variable estimation for linear models by two-stage least-squares (2SLS) regression. The main ivreg() model-fitting function is designed to provide a workflow as similar as possible to standard lm() regression. A wide range of methods is provided for fitted ivreg model objects, including extensive functionality for computing and graphing regression diagnostics in addition to other standard model tools.
AER, effects (>= 4.2.0), knitr, insight, parallel, rmarkdown,
sandwich, testthat

Instrumental-Variables Regression by '2SLS', '2SM', or '2SMM',
with Diagnostics
c(person(given = "John", family = "Fox", role = c("aut", "cre"), email = "jfox@mcmaster.ca", comment = c(ORCID = "0000-0002-1196-8012")),
person(given = "Christian", family = "Kleiber", role = "aut", email = "Christian.Kleiber@unibas.ch", comment = c(ORCID = "0000-0002-6781-4733")),
person(given = "Achim", family = "Zeileis", role = "aut", email = "Achim.Zeileis@R-project.org", comment = c(ORCID = "0000-0003-0918-3766")))
Instrumental variable estimation for linear models by two-stage least-squares (2SLS) regression or by robust-regression via M-estimation (2SM) or MM-estimation (2SMM). The main ivreg() model-fitting function is designed to provide a workflow as similar as possible to standard lm() regression. A wide range of methods is provided for fitted ivreg model objects, including extensive functionality for computing and graphing regression diagnostics in addition to other standard model tools.
car (>= 3.0-9), Formula, lmtest, MASS, stats
AER, effects (>= 4.2.0), knitr, insight, parallel, rmarkdown,
sandwich, testthat, modelsummary, ggplot2