betaNB: Example Using the SCorNB Function
Ivan Jacob Agaloos Pesigan
Source:vignettes/example-s-cor-nb.Rmd
example-s-cor-nb.Rmd
Confidence intervals for semipartial correlation coefficients are
generated using the SCorNB()
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)
Semipartial Correlation Coefficients
Normal-Theory Approach
out <- SCorNB(nb, alpha = 0.05)
Methods
summary
Summary of the results of SCorNB()
.
Percentile Confidence Intervals
summary(out, type = "pc")
#> Call:
#> SCorNB(object = nb, alpha = 0.05)
#>
#> Semipartial correlations
#> type = "pc"
#> est se R 2.5% 97.5%
#> NARTIC 0.4312 0.0707 5000 0.2842 0.5629
#> PCTGRT 0.3430 0.0731 5000 0.1838 0.4744
#> PCTSUPP 0.2385 0.0702 5000 0.0958 0.3689
Bias Corrected Confidence Intervals
summary(out, type = "bc")
#> Call:
#> SCorNB(object = nb, alpha = 0.05)
#>
#> Semipartial correlations
#> type = "bc"
#> est se R 2.5% 97.5%
#> NARTIC 0.4312 0.0707 5000 0.3024 0.5797
#> PCTGRT 0.3430 0.0731 5000 0.2100 0.4996
#> PCTSUPP 0.2385 0.0702 5000 0.1071 0.3856
Bias Corrected and Accelerated Confidence Intervals
summary(out, type = "bca")
#> Call:
#> SCorNB(object = nb, alpha = 0.05)
#>
#> Semipartial correlations
#> type = "bca"
#> est se R 2.5% 97.5%
#> NARTIC 0.4312 0.0707 5000 0.3087 0.5906
#> PCTGRT 0.3430 0.0731 5000 0.2196 0.5138
#> PCTSUPP 0.2385 0.0702 5000 0.1034 0.3822
coef
Return the vector of estimates.
coef(out)
#> NARTIC PCTGRT PCTSUPP
#> 0.4311525 0.3430075 0.2384789
vcov
Return the sampling covariance matrix.
vcov(out)
#> NARTIC PCTGRT PCTSUPP
#> NARTIC 0.0050029466 -0.0004231678 -0.0007344594
#> PCTGRT -0.0004231678 0.0053503126 -0.0008096115
#> PCTSUPP -0.0007344594 -0.0008096115 0.0049346860
confint
Return confidence intervals.
Percentile Confidence Intervals
confint(out, level = 0.95, type = "pc")
#> 2.5 % 97.5 %
#> NARTIC 0.28416656 0.5628525
#> PCTGRT 0.18377442 0.4744038
#> PCTSUPP 0.09578834 0.3688574
Bias Corrected Confidence Intervals
confint(out, level = 0.95, type = "bc")
#> 2.5 % 97.5 %
#> NARTIC 0.3024316 0.5796886
#> PCTGRT 0.2099740 0.4995694
#> PCTSUPP 0.1071179 0.3855923
Bias Corrected and Accelerated Confidence Intervals
confint(out, level = 0.95, type = "bca")
#> 2.5 % 97.5 %
#> NARTIC 0.3087198 0.5906212
#> PCTGRT 0.2196308 0.5138464
#> PCTSUPP 0.1033713 0.3822040