Free step-down re-sampling adjustment for multiple testing in linear regression

This brief post presents a function to implement the free step-down re-sampling p-value adjustment for multiple-testing for regression models. It is an adaptation of the R code presented in Foulkes (2009, pp. 114-119), but it implements the minP method in addition to the maxT method.

Continue reading “Free step-down re-sampling adjustment for multiple testing in linear regression”

Testing R-squared change for linear regression models with heteroscedasticity-consistent standard errors

If you want to test whether the change in R2 is statistically significant for nested linear models with heteroscedasticity-consistent (HC) standard errors (e.g., hierarchical regression), then you can use vcovHC() from the sandwich package and waldtest() from the lmtest package.

Continue reading “Testing R-squared change for linear regression models with heteroscedasticity-consistent standard errors”