regression analysis – R Functions and Packages for Political Science Analysis
Dealing with heteroskedasticity; regression with robust standard errors using R
Dealing with heteroskedasticity; regression with robust standard errors using R
Robust and clustered standard errors with R | Program Evaluation
Group-By Modeling in R Made Easy | r4stats.com
Principles of Econometrics with R
Principles of Econometrics with R
Plot regression models — plot_model • sjPlot
Correct for heteroskedasticity in OLS with sandwich package in R – R Functions and Packages for Political Science Analysis
ご注文は学習済モデルの確認ですか？BROOM【tidymodels, broom】 - Qiita
Non-Constant Variance
Package 'broom'
sandwich: Robust Covariance Matrix Estimators • sandwich
reghdfe and R: The Joys of Standard Error Correction | R-bloggers
robust standard errors: will tidy.coeftest(., conf.int=TRUE) ever be possible? · Issue #663 · tidymodels/broom · GitHub
Robust and clustered standard errors with R | Program Evaluation
Available methods • broom
Robust and clustered standard errors with R | Program Evaluation
Enhancement: easy way to select rows from a tidy data frame · Issue #525 · tidymodels/broom · GitHub
Slides from my talk on the broom package | R-bloggers
modelsummary package - RDocumentation
Ryan Safner - Replicating Stata's 'Robust' Option for OLS Standard Errors in R
HAC (Newey-West) standard errors · Issue #272 · DeclareDesign/estimatr · GitHub
