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clarify
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", "0.2.2") Attach the package and use:
library("clarify")
Maintained by
Noah Greifer
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-01-25
Latest Update: 2024-05-30
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 0.2.2, https://cran.r-project.org/web/packages/clarify. Accessed 18 Sep. 2026.
Previous versions and publish date:
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Complete documentation for clarify
Functions, R codes and Examples using
the clarify R package
Some associated functions: clarify-package . misim . plot.clarify_adrf . plot.clarify_setx . sim . sim_adrf . sim_ame . sim_apply . sim_setx . summary.clarify_est .
Some associated R codes: checks.R . clarify-package.R . clarify_est_methods.R . clarify_predict.R . get_model_components.R . misim.R . plot.clarify_adrf.R . plot.clarify_est.R . plot.clarify_setx.R . sim.R . sim_adrf.R . sim_ame.R . sim_apply.R . sim_setx.R . summary.clarify_est.R . utils.R . zzz.R . Full clarify package functions and examples
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