petersenlab (version 1.1.0)

puc: Percent of Uncontaminated Correlations (PUC).

Description

Percent of uncontaminated correlations (PUC) from bifactor model.

Usage

puc(numItems, numSpecificFactors)

Value

Percent of Uncontaminated Correlations (PUC).

Arguments

numItems

Number of items (or indicators).

numSpecificFactors

Number of specific factors.

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

tools:::Rd_expr_doi("10.31234/osf.io/6tf7j") tools:::Rd_expr_doi("10.1177/0013164412449831") tools:::Rd_expr_doi("10.1037/met0000045")

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

Examples

puc(
  numItems = 9,
  numSpecificFactors = 3
)

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
)