Correct sandwich variance inference by Fay's degrees of freedom correction

Computes the degrees of freedom correction described in Fay and Graubard (2001). See vignette("05_finite_sample_corrections", package = "geex") for further information.

fay_df_correction(components, b = 0.75, L, version)

Arguments

components

an object of class sandwich_components

b

a numeric value < 1. Defaults to 0.75 as in Fay.

L

a k x p matrix where p is the dimension of theta

version

either 1 or 2, corresponding to hat(d) or tilde(d), respectively

Value

a scalar corresponding to the estimated degrees of freedom

References

Fay, M. P., & Graubard, B. I. (2001). Small-Sample adjustments for Wald-type tests using sandwich estimators. Biometrics, 57(4), 1198-1206

Examples

# This example demonstrates usage of the corrections, not a meaningful application
myee <- function(data){
 function(theta){
   c(data$Y1 - theta[1],
   (data$Y1 - theta[1])^2 - theta[2])
  }
}

results <- m_estimate(
   estFUN = myee,
   data = geexex,
   root_control = setup_root_control(start = c(1,1)),
   corrections  = list(
     df_correction1 = correction(fay_df_correction,
                        b = .75, L = c(0, 1), version = 1 ),
     df_correction2 = correction(fay_df_correction,
                        b = .75, L = c(0, 1), version = 2 ))
   )

get_corrections(results)
#> $df_correction1
#> [1] 99
#> 
#> $df_correction2
#> [1] 96.5524
#>