Dealing with heteroskedasticity; regression with robust standard errors using R
Compatibility with stargazer or xtable · Issue #12 · tidymodels/broom · GitHub
Replicating Stata's 'Robust' Option for OLS Standard Errors in R | Ryan Safner
Enhancement: easy way to select rows from a tidy data frame · Issue #525 · tidymodels/broom · GitHub
Principles of Econometrics with R
Slides from my talk on the broom package – Variance Explained
Basic Time Series Models | SpringerLink
Replicating Stata's 'Robust' Option for OLS Standard Errors in R | Ryan Safner
Robust and clustered standard errors with R | Program Evaluation
Robust and clustered standard errors with R | Program Evaluation
sandwich: Robust Covariance Matrix Estimators • sandwich
huxtable/huxreg.Rmd at master · cran/huxtable · GitHub
Dealing with heteroskedasticity; regression with robust standard errors using R
Robust and clustered standard errors with R | Program Evaluation
Principles of Econometrics with R
Mao Wang (@maowang01) / Twitter
robust standard errors: will tidy.coeftest(., conf.int=TRUE) ever be possible? · Issue #663 · tidymodels/broom · GitHub
robust standard errors: will tidy.coeftest(., conf.int=TRUE) ever be possible? · Issue #663 · tidymodels/broom · GitHub
Dealing with heteroskedasticity; regression with robust standard errors using R – R-Craft
Plot regression models — plot_model • sjPlot
Visualization of regression coefficients (in R) | R-bloggers
Principles of Econometrics with R
modelsummary package - RDocumentation
Estimating causal effects from aggregated data | R-bloggers
HAC (Newey-West) standard errors · Issue #272 · DeclareDesign/estimatr · GitHub
Slides from my talk on the broom package | R-bloggers
