Other packages > Find by keyword >

REndo  

Fitting Linear Models with Endogenous Regressors using Latent Instrumental Variables
View on CRAN: Click here


Download and install REndo package within the R console
Install from CRAN:
install.packages("REndo")

Install from Github:
library("remotes")
install_github("cran/REndo")

Install by package version:
library("remotes")
install_version("REndo", "2.4.10")



Attach the package and use:
library("REndo")
Maintained by
Raluca Gui
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2015-12-09
Latest Update: 2023-09-05
Description:
Fits linear models with endogenous regressor using latent instrumental variable approaches. The methods included in the package are Lewbel's (1997) higher moments approach as well as Lewbel's (2012) heteroscedasticity approach, Park and Gupta's (2012) joint estimation method that uses Gaussian copula and Kim and Frees's (2007) multilevel generalized method of moment approach that deals with endogeneity in a multilevel setting. These are statistical techniques to address the endogeneity problem where no external instrumental variables are needed. See the publication related to this package in the Journal of Statistical Software for more details: . Note that with version 2.0.0 sweeping changes were introduced which greatly improve functionality and usability but break backwards compatibility.
How to cite:
Raluca Gui (2015). REndo: Fitting Linear Models with Endogenous Regressors using Latent Instrumental Variables. R package version 2.4.10, https://cran.r-project.org/web/packages/REndo. Accessed 21 Dec. 2024.
Previous versions and publish date:
1.0 (2015-12-09 00:21), 1.1 (2016-11-16 10:49), 1.2 (2017-04-10 16:33), 1.3 (2017-11-08 17:59), 2.0.0 (2018-11-10 15:50), 2.1.0 (2019-01-16 15:50), 2.2.0 (2019-04-14 00:43), 2.2.1 (2019-06-05 16:20), 2.3.0 (2019-08-05 18:00), 2.3.1 (2020-02-17 16:50), 2.4.0 (2020-05-24 17:10), 2.4.1 (2020-10-15 01:40), 2.4.2 (2021-02-10 11:30), 2.4.3 (2021-09-03 23:20), 2.4.5 (2022-05-18 15:40), 2.4.6 (2022-08-23 14:30), 2.4.7 (2022-10-21 09:47), 2.4.8 (2023-02-07 10:42), 2.4.9 (2023-09-05 09:30)
Other packages that cited REndo R package
View REndo citation profile
Other R packages that REndo depends, imports, suggests or enhances
Complete documentation for REndo
Functions, R codes and Examples using the REndo R package
Some associated functions: REndo . confint.rendo.boots . copulaCorrection . dataCopCont . dataCopCont2 . dataCopDis . dataCopDis2 . dataCopDisCont . dataHetIV . dataHigherMoments . dataLatentIV . dataMultilevelIV . hetErrorsIV . higherMomentsIV . latentIV . multilevelIV . predict.rendo.copula.correction . predict.rendo.ivreg . predict.rendo.latent.IV . predict.rendo.multilevel . summary.rendo.copula.correction . summary.rendo.latent.IV . summary.rendo.multilevel . vcov.rendo.boots . 
Some associated R codes: REndo-package.R . RcppExports.R . data.R . f_checkinput_copulacorrection.R . f_checkinput_helperfunctions.R . f_checkinput_heterrorsIV.R . f_checkinput_highermomentsiv.R . f_checkinput_latentIV.R . f_checkinput_multilevel.R . f_copulacorrection_interface.R . f_copulacorrection_linearmodel.R . f_copulacorrection_optimizeLL.R . f_copulacorrectionpstar_continuous.R . f_copulacorrectionpstar_discrete.R . f_formula_helpers.R . f_heterrorsIV.R . f_heterrorsIV_IIV.R . f_highermomentsIV.R . f_highermomentsIV_IIV.R . f_latentIV.R . f_latentIV_LL.R . f_multilevelIV.R . f_multilevel_2levels.R . f_multilevel_3levels.R . f_multilevel_gmmestim.R . f_multilevel_helpers.R . f_multilevel_omittedvar.R . f_new_copulacorrection.R . f_new_multilevel.R . f_new_rendobase.R . f_new_rendoboots.R . f_new_rendoivreg.R . f_new_rendolatentIV.R . f_s3_multilevel.R . f_s3_rendobase.R . f_s3_rendoboots.R . f_s3_rendocopulacorrection.R . f_s3_rendoivreg.R . f_s3_rendolatentIV.R .  Full REndo package functions and examples
Downloads during the last 30 days
Get rewarded with contribution points by helping add
Reviews / comments / questions /suggestions ↴↴↴

Today's Hot Picks in Authors and Packages

helda  
Preprocess Data and Get Better Insights from Machine Learning Models
The main focus is on preprocessing and data visualization of machine learning models performances.So ...
Download / Learn more Package Citations See dependency  
SEIRfansy  
Extended Susceptible-Exposed-Infected-Recovery Model
Extended Susceptible-Exposed-Infected-Recovery Model for handling high false negative rate and symp ...
Download / Learn more Package Citations See dependency  
r2resize  
In-Text Resize for Images, Tables and Fancy Resize Containers in 'shiny', 'rmarkdown' and 'quarto' Documents
Automatic resizing toolbar for containers, images and tables. Various resizable or expandable contai ...
Download / Learn more Package Citations See dependency  
condGEE  
Parameter Estimation in Conditional GEE for Recurrent Event Gap Times
Solves for the mean parameters, the variance parameter, and their asymptotic variance in a condition ...
Download / Learn more Package Citations See dependency  
CIFsmry  
Weighted summary of cumulative incidence functions
Estimate of cumulative incidence function in two samples. Provide weighted summary statistics based ...
Download / Learn more Package Citations See dependency  
batteryreduction  
An R Package for Data Reduction by Battery Reduction
Battery reduction is a method used in data reduction. It uses Gram-Schmidt orthogonal rotations to f ...
Download / Learn more Package Citations See dependency  

23,394

R Packages

201,798

Dependencies

63,416

Author Associations

23,395

Publication Badges

© Copyright 2022 - present. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA