Dealing with heteroskedasticity; regression with robust standard errors using R
cluster computing - How to create an linear model output with clustered (by firms) standard error in R - Stack Overflow
Analyse Pseudo-R2, VIF scores and robust standard errors for generalised linear models in R – R Functions and Packages for Political Science Analysis
Heteroskedasticity-robust standard errors | Assumptions and derivation
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Robust and clustered standard errors with R | Program Evaluation
diagnostics – R Functions and Packages for Political Science Analysis
robust standard errors: will tidy.coeftest(., conf.int=TRUE) ever be possible? · Issue #663 · tidymodels/broom · GitHub
Ryan Safner - Replicating Stata's 'Robust' Option for OLS Standard Errors in R
Tools for summarizing and visualizing regression models • jtools
Tools for summarizing and visualizing regression models
PDF) Extracting, Computing and Exploring the Parameters of Statistical Models using R
Robust and clustered standard errors with R | Program Evaluation
Dealing with heteroskedasticity; regression with robust standard errors using R
ECON61001 Robust standard errors - YouTube
Dealing with heteroskedasticity; regression with robust standard errors using R
Adjustments of already-adjusted standard errors · Issue #280 · vincentarelbundock/modelsummary · GitHub
Robust and clustered standard errors with R | Program Evaluation
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Robust and clustered standard errors with R | Program Evaluation
README
robust standard errors: will tidy.coeftest(., conf.int=TRUE) ever be possible? · Issue #663 · tidymodels/broom · GitHub
