Package: estimatr 1.0.4

Graeme Blair

estimatr: Fast Estimators for Design-Based Inference

Fast procedures for small set of commonly-used, design-appropriate estimators with robust standard errors and confidence intervals. Includes estimators for linear regression, instrumental variables regression, difference-in-means, Horvitz-Thompson estimation, and regression improving precision of experimental estimates by interacting treatment with centered pre-treatment covariates introduced by Lin (2013) <doi:10.1214/12-AOAS583>.

Authors:Graeme Blair [aut, cre], Jasper Cooper [aut], Alexander Coppock [aut], Macartan Humphreys [aut], Luke Sonnet [aut], Neal Fultz [ctb], Lily Medina [ctb], Russell Lenth [ctb]

estimatr_1.0.4.tar.gz
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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
estimatr/json (API)

# Install 'estimatr' in R:

install.packages('estimatr', repos = c('https://declaredesign.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/declaredesign/estimatr/issues

Pkgdown/docs site:https://declaredesign.org

Uses libs:

c++– GNU Standard C++ Library v3

Datasets:

alo_star_men - Replication data for Lin 2013

On CRAN:

cpp

11.77 score 135 stars 15 packages 3.3k scripts 14k downloads 3 mentions 16 exports 5 dependencies

Last updated from:10a18f124e. Checks:13 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	200
linux-devel-x86_64	OK	205
source / vignettes	OK	234
linux-release-arm64	OK	187
linux-release-x86_64	OK	199
macos-release-arm64	OK	139
macos-release-x86_64	OK	357
macos-oldrel-arm64	OK	128
macos-oldrel-x86_64	OK	388
windows-devel	OK	160
windows-release	OK	189
windows-oldrel	OK	158
wasm-release	OK	171

Exports:commarobust declaration_to_condition_pr_mat difference_in_means extract.iv_robust extract.lm_robust gen_pr_matrix_cluster glance horvitz_thompson iv_robust lh_robust lm_lin lm_robust lm_robust_fit permutations_to_condition_pr_mat starprep tidy

Dependencies:Formula generics Rcpp RcppEigen rlang

Help page	Topics
Replication data for Lin 2013	alo_star_men
Build lm_robust object from lm fit	commarobust
Builds condition probability matrices for Horvitz-Thompson estimation from 'randomizr' declaration	declaration_to_condition_pr_mat
Design-based difference-in-means estimator	difference_in_means
estimatr	estimatr-package estimatr
Glance at an estimatr object	estimatr_glancers glance.difference_in_means glance.horvitz_thompson glance.iv_robust glance.lh_robust glance.lm_robust
Tidy an estimatr object	estimatr_tidiers tidy.difference_in_means tidy.horvitz_thompson tidy.iv_robust tidy.lh tidy.lh_robust tidy.lm_robust
Extract model data for 'texreg' package	extract.iv_robust extract.lm_robust extract.robust_default
Generate condition probability matrix given clusters and probabilities	gen_pr_matrix_cluster
Horvitz-Thompson estimator for two-armed trials	horvitz_thompson
Two-Stage Least Squares Instrumental Variables Regression	iv_robust
Linear Hypothesis for Ordinary Least Squares with Robust Standard Errors	lh_robust
Linear regression with the Lin (2013) covariate adjustment	lm_lin
Ordinary Least Squares with Robust Standard Errors	lm_robust
Internal method that creates linear fits	lm_robust_fit
Extra logging on na.omit handler	na.omit_detailed.data.frame
Builds condition probability matrices for Horvitz-Thompson estimation from permutation matrix	permutations_to_condition_pr_mat
Predict method for 'lm_robust' object	predict.lm_robust
Prepare model fits for stargazer	starprep

Package: estimatr 1.0.4

estimatr: Fast Estimators for Design-Based Inference

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