Skip to contents

Confidence intervals for squared partial correlation coefficients are generated using the PCorNB() function from the betaNB package. In this example, we use the data set and the model used in betaNB: Example Using the BetaNB Function.

df <- betaNB::nas1982

Regression

Fit the regression model using the lm() function.

object <- lm(QUALITY ~ NARTIC + PCTGRT + PCTSUPP, data = df)

Nonparametric Bootstrap

nb <- NB(object)

Squared Partial Correlation Coefficients

Normal-Theory Approach

out <- PCorNB(nb, alpha = 0.05)

Methods

summary

Summary of the results of PCorNB().

Percentile Confidence Intervals

summary(out, type = "pc")
#> Call:
#> PCorNB(object = nb, alpha = 0.05)
#> 
#> Squared partial correlations
#> type = "pc"
#>            est     se    R   2.5%  97.5%
#> NARTIC  0.4874 0.0982 5000 0.2872 0.6648
#> PCTGRT  0.3757 0.1081 5000 0.1609 0.5829
#> PCTSUPP 0.2254 0.1159 5000 0.0403 0.4849

Bias Corrected Confidence Intervals

summary(out, type = "bc")
#> Call:
#> PCorNB(object = nb, alpha = 0.05)
#> 
#> Squared partial correlations
#> type = "bc"
#>            est     se    R   2.5%  97.5%
#> NARTIC  0.4874 0.0982 5000 0.2691 0.6525
#> PCTGRT  0.3757 0.1081 5000 0.1528 0.5759
#> PCTSUPP 0.2254 0.1159 5000 0.0346 0.4704

Bias Corrected and Accelerated Confidence Intervals

summary(out, type = "bca")
#> Call:
#> PCorNB(object = nb, alpha = 0.05)
#> 
#> Squared partial correlations
#> type = "bca"
#>            est     se    R   2.5%  97.5%
#> NARTIC  0.4874 0.0982 5000 0.2697 0.6526
#> PCTGRT  0.3757 0.1081 5000 0.1602 0.5821
#> PCTSUPP 0.2254 0.1159 5000 0.0212 0.4423

coef

Return the vector of estimates.

coef(out)
#>    NARTIC    PCTGRT   PCTSUPP 
#> 0.4874382 0.3757383 0.2253739

vcov

Return the sampling covariance matrix.

vcov(out)
#>              NARTIC       PCTGRT      PCTSUPP
#> NARTIC  0.009639565 0.0014808200 0.0021051605
#> PCTGRT  0.001480820 0.0116898519 0.0006933677
#> PCTSUPP 0.002105160 0.0006933677 0.0134260204

confint

Return confidence intervals.

Percentile Confidence Intervals

confint(out, level = 0.95, type = "pc")
#>              2.5 %    97.5 %
#> NARTIC  0.28720172 0.6647768
#> PCTGRT  0.16091920 0.5829195
#> PCTSUPP 0.04026216 0.4849199

Bias Corrected Confidence Intervals

confint(out, level = 0.95, type = "bc")
#>              2.5 %    97.5 %
#> NARTIC  0.26905184 0.6525084
#> PCTGRT  0.15277864 0.5759113
#> PCTSUPP 0.03461796 0.4703940

Bias Corrected and Accelerated Confidence Intervals

confint(out, level = 0.95, type = "bca")
#>              2.5 %    97.5 %
#> NARTIC  0.26967574 0.6526185
#> PCTGRT  0.16021333 0.5820753
#> PCTSUPP 0.02116022 0.4422629

References