Learn R Programming

⚠️There's a newer version (1.0.6) of this package.Take me there.

estimatr (version 0.6.0)

Fast Estimators for Design-Based Inference

Description

Fast procedures for small set of commonly-used, design-appropriate estimators with robust standard errors and confidence intervals. Includes estimators for linear regression, regression improving precision of experimental estimates by interacting treatment with centered pre-treatment covariates introduced by Lin (2013) , difference-in-means, and Horvitz-Thompson estimation.

Copy Link

Version

Install

install.packages('estimatr')

Monthly Downloads

14,086

Version

0.6.0

License

MIT + file LICENSE

Issues

Pull Requests

Stars

Forks

Repository

https://github.com/DeclareDesign/estimatr

Homepage

http://estimatr.declaredesign.org

Maintainer

Graeme Blair

Last Published

March 28th, 2018

Functions in estimatr (0.6.0)

Replication data for Lin 2013

declaration_to_condition_pr_mat

Builds condition probability matrices for Horvitz-Thompson estimation from randomizr declaration

horvitz_thompson

Horvitz-Thompson estimator for two-armed trials

Two-Stage Least Squares Instrumental Variables Regression

difference_in_means

Design-based difference-in-means estimator

extract.lm_robust

Extract model data for texreg package

Internal method that creates linear fits

permutations_to_condition_pr_mat

Builds condition probability matrices for Horvitz-Thompson estimation from permutation matrix

na.omit_detailed.data.frame

Extra logging on na.omit handler

gen_pr_matrix_cluster

Generate condition probability matrix given clusters and probabilities

predict.lm_robust

Predict method for lm_robust object

Linear regression with the Lin (2013) covariate adjustment

Ordinary Least Squares with Robust Standard Errors

Tidy the result of an estimator into a data.frame