Percent of Uncontaminated Correlations (PUC).

Percent of uncontaminated correlations (PUC) from bifactor model.

Usage

puc(numItems, numSpecificFactors)

Arguments

numItems

Number of items (or indicators).

numSpecificFactors

Number of specific factors.

Value

Percent of Uncontaminated Correlations (PUC).

Details

Estimates the percent of uncontaminated correlations (PUC) from a bifactor model. The PUC represents the percentage of correlations (i.e., covariance terms) that reflect variance from only the general factor (i.e., not variance from a specific factor). Correlations that are explained by the specific factors are considered "contaminated" by multidimensionality.

See also

doi:10.31234/osf.io/6tf7j doi:10.1177/0013164412449831 doi:10.1037/met0000045

Other structural equation modeling: equiv_chi(), make_esem_model(), measurementNoninvarianceEffectSize(), satorraBentlerScaledChiSquareDifferenceTestStatistic(), semPlotInteraction()

Examples

puc(
  numItems = 9,
  numSpecificFactors = 3
)
#> [1] 0.75

mydata <- data.frame(
  numItems = c(9,18,18,36,36,36),
  numSpecificFactors = c(3,3,6,3,6,12)
)

puc(
  numItems = mydata$numItems,
  numSpecificFactors = mydata$numSpecificFactors
)
#> [1] 0.7500000 0.7058824 0.8823529 0.6857143 0.8571429 0.9428571