coef_test {clubSandwich}

Test all or selected regression coefficients in a fitted model

Description

coef_test reports t-tests for each coefficient estimate in a fitted linear regression model, using a sandwich estimator for the standard errors and a small sample correction for the p-value. The small-sample correction is based on a Satterthwaite approximation or a saddlepoint approximation.

Usage

coef_test(
  obj,
  vcov,
  test = "Satterthwaite",
  coefs = "All",
  p_values = TRUE,
  ...
)

Arguments

obj

Fitted model for which to calculate t-tests.

vcov

Variance covariance matrix estimated using vcovCR or a character string specifying which small-sample adjustment should be used to calculate the variance-covariance.

test

Character vector specifying which small-sample corrections to calculate. "z" returns a z test (i.e., using a standard normal reference distribution). "naive-t" returns a t test with m - 1 degrees of freedom, where m is the number of unique clusters. "naive-tp" returns a t test with m - p degrees of freedom, where p is the number of regression coefficients in obj. "Satterthwaite" returns a Satterthwaite correction. "saddlepoint" returns a saddlepoint correction. Default is "Satterthwaite".

coefs

Character, integer, or logical vector specifying which coefficients should be tested. The default value "All" will test all estimated coefficients.

p_values

Logical indicating whether to report p-values. The default value is TRUE.

...

Further arguments passed to vcovCR, which are only needed if vcov is a character string.

Value

A data frame containing estimated regression coefficients, standard errors, and test results. For the Satterthwaite approximation, degrees of freedom and a p-value are reported. For the saddlepoint approximation, the saddlepoint and a p-value are reported.

See Also

vcovCR

Examples

data("ChickWeight", package = "datasets")
lm_fit <- lm(weight ~ Diet  * Time, data = ChickWeight)
diet_index <- grepl("Diet.:Time", names(coef(lm_fit)))
coef_test(lm_fit, vcov = "CR2", cluster = ChickWeight$Chick, coefs = diet_index)

V_CR2 <- vcovCR(lm_fit, cluster = ChickWeight$Chick, type = "CR2")
coef_test(lm_fit, vcov = V_CR2, coefs = diet_index)