Diagnostics and Remedial Measures
Dealing with heteroskedasticity; regression with robust standard errors using R
Compatibility with stargazer or xtable · Issue #12 · tidymodels/broom · GitHub
Principles of Econometrics with R
Robust and clustered standard errors with R | Program Evaluation
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
HAC (Newey-West) standard errors · Issue #272 · DeclareDesign/estimatr · GitHub
Robust and clustered standard errors with R | Program Evaluation
modelsummary package - RDocumentation
regression - R: Confused about robust standard errors using “felm” and “huxreg” - Cross Validated
Ryan Safner - Replicating Stata's 'Robust' Option for OLS Standard Errors in R
Dealing with heteroskedasticity; regression with robust standard errors using R
Module 5: Regression analysis and data visualization
Group-By Modeling in R Made Easy | r4stats.com
Principles of Econometrics with R
sandwich: Robust Covariance Matrix Estimators • sandwich
RPubs - Doing More with Regression Output in R
Robust and clustered standard errors with R | Program Evaluation
Robust and clustered standard errors with R | Program Evaluation
Non-Constant Variance
Regression table with clustered standard errors in R jupyter notebook? - Stack Overflow
Slides from my talk on the broom package – Variance Explained
broom presentation
