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betaNB: Example Using the BetaNB Function

Ivan Jacob Agaloos Pesigan

Source: vignettes/example-beta-nb.Rmd
example-beta-nb.Rmd

In this example, a multiple regression model is fitted using program quality ratings (QUALITY) as the regressand/outcome variable and number of published articles attributed to the program faculty members (NARTIC), percent of faculty members holding research grants (PCTGRT), and percentage of program graduates who received support (PCTSUPP) as regressor/predictor variables using a data set from 1982 ratings of 46 doctoral programs in psychology in the USA (National Research Council, 1982). Confidence intervals for the standardized regression coefficients are generated using the BetaNB() function from the betaNB package.

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)

Standardized Regression Slopes 

out <- BetaNB(nb, alpha = 0.05)

Methods

summary

Summary of the results of BetaNB().

Percentile Confidence Intervals 

summary(out, type = "pc")
#> Call:
#> BetaNB(object = nb, alpha = 0.05)
#> 
#> Standardized regression slopes
#> type = "pc"
#>            est     se    R   2.5%  97.5%
#> NARTIC  0.4951 0.0721 5000 0.3534 0.6393
#> PCTGRT  0.3915 0.0763 5000 0.2353 0.5364
#> PCTSUPP 0.2632 0.0792 5000 0.1038 0.4172

Bias Corrected Confidence Intervals 

summary(out, type = "bc")
#> Call:
#> BetaNB(object = nb, alpha = 0.05)
#> 
#> Standardized regression slopes
#> type = "bc"
#>            est     se    R   2.5%  97.5%
#> NARTIC  0.4951 0.0721 5000 0.3531 0.6391
#> PCTGRT  0.3915 0.0763 5000 0.2339 0.5354
#> PCTSUPP 0.2632 0.0792 5000 0.1106 0.4241

Bias Corrected and Accelerated Confidence Intervals 

summary(out, type = "bca")
#> Call:
#> BetaNB(object = nb, alpha = 0.05)
#> 
#> Standardized regression slopes
#> type = "bca"
#>            est     se    R   2.5%  97.5%
#> NARTIC  0.4951 0.0721 5000 0.3547 0.6404
#> PCTGRT  0.3915 0.0763 5000 0.2376 0.5405
#> PCTSUPP 0.2632 0.0792 5000 0.1024 0.4156

coef

Return the vector of estimates.

coef(out)
#>    NARTIC    PCTGRT   PCTSUPP 
#> 0.4951451 0.3914887 0.2632477

vcov

Return the sampling covariance matrix.

vcov(out)
#>               NARTIC       PCTGRT      PCTSUPP
#> NARTIC   0.005195205 -0.003051844 -0.001843138
#> PCTGRT  -0.003051844  0.005822920 -0.002077258
#> PCTSUPP -0.001843138 -0.002077258  0.006272927

confint

Return confidence intervals.

Percentile Confidence Intervals 

confint(out, level = 0.95, type = "pc")
#>             2.5 %    97.5 %
#> NARTIC  0.3533981 0.6393364
#> PCTGRT  0.2352860 0.5363628
#> PCTSUPP 0.1038004 0.4172450

Bias Corrected Confidence Intervals 

confint(out, level = 0.95, type = "bc")
#>             2.5 %    97.5 %
#> NARTIC  0.3530575 0.6390519
#> PCTGRT  0.2338723 0.5353540
#> PCTSUPP 0.1106477 0.4241144

Bias Corrected and Accelerated Confidence Intervals 

confint(out, level = 0.95, type = "bca")
#>             2.5 %    97.5 %
#> NARTIC  0.3547319 0.6404196
#> PCTGRT  0.2376124 0.5405394
#> PCTSUPP 0.1023588 0.4156483

References