Estimate Squared Partial Correlation Coefficients and the Corresponding Sampling Covariance Matrix

Estimate Squared Partial Correlation Coefficients and the Corresponding Sampling Covariance Matrix

Usage

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

Arguments

object

Object of class betadelta, that is, the output of the BetaDelta() function.

alpha

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

Value

Returns an object of class esdelta 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 ("PCorDelta").

Details

The sampling covariance matrix is obtained by the delta method from the sampling covariance matrix of the variances and covariances stored in object (normal-theory or asymptotically distribution-free). Two or more regressors are required.

See also

Other Beta Delta Functions: BetaDelta(), DeltaRSqDelta(), DiffBetaDelta(), FSqDelta(), RSqDelta(), SCorDelta()

Author

Ivan Jacob Agaloos Pesigan

Examples

object <- lm(QUALITY ~ NARTIC + PCTGRT + PCTSUPP, data = nas1982)
std <- BetaDelta(object)
out <- PCorDelta(std)
# Methods -------------------------------------------------------
print(out)
#> Call:
#> PCorDelta(object = std)
#> 
#> Squared partial correlations with MVN standard errors:
#>            est     se      z      p   0.05%    0.5%   2.5%  97.5%  99.5% 99.95%
#> NARTIC  0.4874 0.1055 4.6192 0.0000  0.1402  0.2156 0.2806 0.6943 0.7593 0.8347
#> PCTGRT  0.3757 0.1128 3.3299 0.0009  0.0044  0.0851 0.1546 0.5969 0.6664 0.7470
#> PCTSUPP 0.2254 0.1084 2.0783 0.0377 -0.1315 -0.0540 0.0128 0.4379 0.5047 0.5822
summary(out)
#> Call:
#> PCorDelta(object = std)
#> 
#> Squared partial correlations with MVN standard errors:
#>            est     se      z      p   0.05%    0.5%   2.5%  97.5%  99.5% 99.95%
#> NARTIC  0.4874 0.1055 4.6192 0.0000  0.1402  0.2156 0.2806 0.6943 0.7593 0.8347
#> PCTGRT  0.3757 0.1128 3.3299 0.0009  0.0044  0.0851 0.1546 0.5969 0.6664 0.7470
#> PCTSUPP 0.2254 0.1084 2.0783 0.0377 -0.1315 -0.0540 0.0128 0.4379 0.5047 0.5822
coef(out)
#>    NARTIC    PCTGRT   PCTSUPP 
#> 0.4874382 0.3757383 0.2253739 
vcov(out)
#>               NARTIC        PCTGRT       PCTSUPP
#> NARTIC  0.0111356142  4.891979e-04  1.943878e-04
#> PCTGRT  0.0004891979  1.273271e-02 -7.224846e-05
#> PCTSUPP 0.0001943878 -7.224846e-05  1.175953e-02
confint(out, level = 0.95)
#>              2.5 %    97.5 %
#> NARTIC  0.28061220 0.6942642
#> PCTGRT  0.15457732 0.5968994
#> PCTSUPP 0.01283274 0.4379151