Other packages > Find by keyword >

clarify  

Simulation-Based Inference for Regression Models
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("clarify", "0.2.1")



Attach the package and use:
library("clarify")
Maintained by
Noah Greifer
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-01-25
Latest Update: 2023-09-21
Description:
Performs simulation-based inference as an alternative to the delta method for obtaining valid confidence intervals and p-values for regression post-estimation quantities, such as average marginal effects and predictions at representative values. This framework for simulation-based inference is especially useful when the resulting quantity is not normally distributed and the delta method approximation fails. The methodology is described in King, Tomz, and Wittenberg (2000) . 'clarify' is meant to replace some of the functionality of the archived package 'Zelig'; see the vignette "Translating Zelig to clarify" for replicating this functionality.
How to cite:
Noah Greifer (2023). clarify: Simulation-Based Inference for Regression Models. R package version 0.2.1, https://cran.r-project.org/web/packages/clarify. Accessed 22 Dec. 2024.
Previous versions and publish date:
0.1.0 (2023-01-25 11:10), 0.1.1 (2023-02-03 14:22), 0.1.2 (2023-02-22 16:40), 0.1.3 (2023-05-04 08:50), 0.2.0 (2023-09-21 22:10)
Other packages that cited clarify R package
View clarify citation profile
Other R packages that clarify depends, imports, suggests or enhances
Complete documentation for clarify
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

wordspace  
Distributional Semantic Models in R
An interactive laboratory for research on distributional semantic models ('DSM', see < ...
Download / Learn more Package Citations See dependency  
dmlalg  
Double Machine Learning Algorithms
Implementation of double machine learning (DML) algorithms in R, based on Emmenegger and Buehlmann ...
Download / Learn more Package Citations See dependency  
composits  
Compositional, Multivariate and Univariate Time Series Outlier Ensemble
A compositional multivariate and univariate time series outlier ensemble.It uses the four R packages ...
Download / Learn more Package Citations See dependency  
elect  
Estimation of Life Expectancies Using Multi-State Models
Functions to compute state-specific and marginal life expectancies. The computation is based on a fi ...
Download / Learn more Package Citations See dependency  
tropAlgebra  
Tropical Algebraic Functions
It includes functions like tropical addition, tropical multiplication for vectors and matrices. In t ...
Download / Learn more Package Citations See dependency  
LOGANTree  
Tree-Based Models for the Analysis of Log Files from Computer-Based Assessments
Enables researchers to model log-file data from computer-based assessments using machine-learning te ...
Download / Learn more Package Citations See dependency  
Maintainer: Qi Qin (view profile)

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