Estimate Semipartial Correlation Coefficients and the Corresponding Sampling Covariance Matrix

Estimate Semipartial Correlation Coefficients and the Corresponding Sampling Covariance Matrix

Usage

SCorSandwich(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 semipartial correlation coefficients.

est

Vector of semipartial correlation coefficients.

fun

Function used ("SCorSandwich").

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). Two or more regressors are required.

See also

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

Author

Ivan Jacob Agaloos Pesigan

Examples

object <- lm(QUALITY ~ NARTIC + PCTGRT + PCTSUPP, data = nas1982)
std <- BetaHC(object)
out <- SCorSandwich(std)
# Methods -------------------------------------------------------
print(out)
#> Call:
#> SCorSandwich(object = std)
#> 
#> Semipartial correlations with HC3 standard errors:
#>            est     se      z      p   0.05%   0.5%   2.5%  97.5%  99.5% 99.95%
#> NARTIC  0.4312 0.0794 5.4303 0.0000  0.1699 0.2266 0.2755 0.5868 0.6357 0.6924
#> PCTGRT  0.3430 0.0789 4.3468 0.0000  0.0834 0.1397 0.1883 0.4977 0.5463 0.6027
#> PCTSUPP 0.2385 0.0783 3.0465 0.0023 -0.0191 0.0368 0.0851 0.3919 0.4401 0.4961
summary(out)
#> Call:
#> SCorSandwich(object = std)
#> 
#> Semipartial correlations with HC3 standard errors:
#>            est     se      z      p   0.05%   0.5%   2.5%  97.5%  99.5% 99.95%
#> NARTIC  0.4312 0.0794 5.4303 0.0000  0.1699 0.2266 0.2755 0.5868 0.6357 0.6924
#> PCTGRT  0.3430 0.0789 4.3468 0.0000  0.0834 0.1397 0.1883 0.4977 0.5463 0.6027
#> PCTSUPP 0.2385 0.0783 3.0465 0.0023 -0.0191 0.0368 0.0851 0.3919 0.4401 0.4961
coef(out)
#>    NARTIC    PCTGRT   PCTSUPP 
#> 0.4311525 0.3430075 0.2384789 
vcov(out)
#>                NARTIC        PCTGRT       PCTSUPP
#> NARTIC   0.0063040434 -0.0002532449 -0.0004374935
#> PCTGRT  -0.0002532449  0.0062268718 -0.0010139363
#> PCTSUPP -0.0004374935 -0.0010139363  0.0061275595
confint(out, level = 0.95)
#>              2.5 %    97.5 %
#> NARTIC  0.27553526 0.5867697
#> PCTGRT  0.18834573 0.4976693
#> PCTSUPP 0.08505544 0.3919024