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Estimate Squared Partial Correlation Coefficients and the Corresponding Sampling Covariance Matrix

Usage

PCorSandwich(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 squared partial correlation coefficients.

est

Vector of squared partial correlation coefficients.

fun

Function used ("PCorSandwich").

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.

Author

Ivan Jacob Agaloos Pesigan

Examples

object <- lm(QUALITY ~ NARTIC + PCTGRT + PCTSUPP, data = nas1982)
std <- BetaHC(object)
out <- PCorSandwich(std)
# Methods -------------------------------------------------------
print(out)
#> Call:
#> PCorSandwich(object = std)
#> 
#> Squared partial correlations with HC3 standard errors:
#>            est     se      z      p   0.05%    0.5%    2.5%  97.5%  99.5%
#> NARTIC  0.4874 0.1095 4.4532 0.0000  0.1273  0.2055  0.2729 0.7020 0.7694
#> PCTGRT  0.3757 0.1156 3.2500 0.0012 -0.0047  0.0779  0.1491 0.6023 0.6735
#> PCTSUPP 0.2254 0.1277 1.7647 0.0776 -0.1949 -0.1036 -0.0249 0.4757 0.5543
#>         99.95%
#> NARTIC  0.8476
#> PCTGRT  0.7562
#> PCTSUPP 0.6456
summary(out)
#> Call:
#> PCorSandwich(object = std)
#> 
#> Squared partial correlations with HC3 standard errors:
#>            est     se      z      p   0.05%    0.5%    2.5%  97.5%  99.5%
#> NARTIC  0.4874 0.1095 4.4532 0.0000  0.1273  0.2055  0.2729 0.7020 0.7694
#> PCTGRT  0.3757 0.1156 3.2500 0.0012 -0.0047  0.0779  0.1491 0.6023 0.6735
#> PCTSUPP 0.2254 0.1277 1.7647 0.0776 -0.1949 -0.1036 -0.0249 0.4757 0.5543
#>         99.95%
#> NARTIC  0.8476
#> PCTGRT  0.7562
#> PCTSUPP 0.6456
coef(out)
#>    NARTIC    PCTGRT   PCTSUPP 
#> 0.4874382 0.3757383 0.2253739 
vcov(out)
#>              NARTIC       PCTGRT      PCTSUPP
#> NARTIC  0.011980986 0.0021633722 0.0027577200
#> PCTGRT  0.002163372 0.0133662295 0.0007428294
#> PCTSUPP 0.002757720 0.0007428294 0.0163111322
confint(out, level = 0.95)
#>               2.5 %    97.5 %
#> NARTIC   0.27290509 0.7019714
#> PCTGRT   0.14914218 0.6023345
#> PCTSUPP -0.02494295 0.4756908