puc: Percent of Uncontaminated Correlations (PUC).

In petersenlab: A Collection of R Functions by the Petersen Lab

Percent of Uncontaminated Correlations (PUC).

Description

Percent of uncontaminated correlations (PUC) from bifactor model.

Usage

puc(numItems, numSpecificFactors)

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.

Value

Percent of Uncontaminated Correlations (PUC).

See Also

\Sexpr[results=rd]{tools:::Rd_expr_doi("10.31234/osf.io/6tf7j")} \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1177/0013164412449831")} \Sexpr[results=rd]{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
)

petersenlab documentation built on April 4, 2025, 12:22 a.m.