Estimate Cohen's f-Squared and Local f-Squared and the Corresponding Sampling Covariance Matrix

Estimate Cohen's f-Squared and Local f-Squared and the Corresponding Sampling Covariance Matrix

Usage

FSqSandwich(object, alpha = c(0.05, 0.01, 0.001))

Arguments

object

Object of class betasandwich, that is, the output of the BetaHC(), BetaN(), or BetaADF() functions.

alpha

Numeric vector. Significance level \(\alpha\).

Value

Returns an object of class essandwich which is a list with the following elements:

call

Function call.

fit

The argument object.

args

Function arguments.

vcov

Sampling covariance matrix of Cohen's f-squared (fsq) and the local f-squared of each regressor.

est

Vector of Cohen's f-squared (fsq) and the local f-squared of each regressor.

fun

Function used ("FSqSandwich").

Details

The sampling covariance matrix is obtained by the delta method from the sampling covariance matrix of the standardized parameters stored in object (normal-theory, asymptotically distribution-free, or heteroskedasticity-consistent).

See also

Other Beta Sandwich Functions: BetaADF(), BetaHC(), BetaN(), DeltaRSqSandwich(), DiffBetaSandwich(), PCorSandwich(), RSqSandwich(), SCorSandwich()

Author

Ivan Jacob Agaloos Pesigan

Examples

object <- lm(QUALITY ~ NARTIC + PCTGRT + PCTSUPP, data = nas1982)
std <- BetaHC(object)
out <- FSqSandwich(std)
# Methods -------------------------------------------------------
print(out)
#> Call:
#> FSqSandwich(object = std)
#> 
#> Cohen's f-squared (fsq) and local f-squared with HC3 standard errors:
#>            est     se      z      p   0.05%    0.5%    2.5%  97.5%  99.5%
#> fsq     4.1158 1.5009 2.7422 0.0061 -0.8229  0.2497  1.1741 7.0575 7.9818
#> NARTIC  0.9510 0.4166 2.2825 0.0225 -0.4200 -0.1222  0.1344 1.7676 2.0242
#> PCTGRT  0.6019 0.2967 2.0288 0.0425 -0.3743 -0.1623  0.0204 1.1834 1.3661
#> PCTSUPP 0.2909 0.2128 1.3670 0.1716 -0.4094 -0.2573 -0.1262 0.7081 0.8392
#>         99.95%
#> fsq     9.0545
#> NARTIC  2.3219
#> PCTGRT  1.5781
#> PCTSUPP 0.9913
summary(out)
#> Call:
#> FSqSandwich(object = std)
#> 
#> Cohen's f-squared (fsq) and local f-squared with HC3 standard errors:
#>            est     se      z      p   0.05%    0.5%    2.5%  97.5%  99.5%
#> fsq     4.1158 1.5009 2.7422 0.0061 -0.8229  0.2497  1.1741 7.0575 7.9818
#> NARTIC  0.9510 0.4166 2.2825 0.0225 -0.4200 -0.1222  0.1344 1.7676 2.0242
#> PCTGRT  0.6019 0.2967 2.0288 0.0425 -0.3743 -0.1623  0.0204 1.1834 1.3661
#> PCTSUPP 0.2909 0.2128 1.3670 0.1716 -0.4094 -0.2573 -0.1262 0.7081 0.8392
#>         99.95%
#> fsq     9.0545
#> NARTIC  2.3219
#> PCTGRT  1.5781
#> PCTSUPP 0.9913
coef(out)
#>       fsq    NARTIC    PCTGRT   PCTSUPP 
#> 4.1157764 0.9509843 0.6018924 0.2909455 
vcov(out)
#>               fsq     NARTIC      PCTGRT     PCTSUPP
#> fsq     2.2526623 0.34629953 0.180617270 0.141603544
#> NARTIC  0.3462995 0.17358320 0.021130291 0.017493371
#> PCTGRT  0.1806173 0.02113029 0.088012079 0.003176666
#> PCTSUPP 0.1416035 0.01749337 0.003176666 0.045301824
confint(out, level = 0.95)
#>               2.5 %    97.5 %
#> fsq      1.17409165 7.0574612
#> NARTIC   0.13439832 1.7675703
#> PCTGRT   0.02043322 1.1833516
#> PCTSUPP -0.12621769 0.7081086