qgraph (version 1.9.8)

cor_auto: Automatically compute an apppropriate correlation matrix

Description

This is mainly a wrapper around Lavaan function lavCor (Rosseel, 2012) to compute a correlation matrix based on pychoric, polyserial and/or Pearson correlations. The wrapper removes all factors and searches for possible ordinal variabes. A variable is classified as ordinal if it is either ordered or if it consist of at most 7 unique integer values. After computing the correlations an additional check will be performed to see if the correlation matrix is positive definite.

Usage

cor_auto(data, select, detectOrdinal = TRUE, ordinalLevelMax = 7, npn.SKEPTIC = FALSE, 
          forcePD = FALSE, missing = "pairwise", verbose = TRUE)

Value

A correlation matrix

Arguments

data

A data frame

select

Variables to select from the data frame (as used in subset)

detectOrdinal

Logical, should ordinal variables be detected? If FALSE only variables that are ordered are treated as ordinal variables

ordinalLevelMax

Integer specyfying the amount of unique integer values a variable should have to be classified as ordinal

npn.SKEPTIC

Logical, should the Nonparanormal SKEPTIC from the huge package be applied if the data is continuous? See huge.npn (Zhao, Liu, Roeder, Lafferty and Wasserman, 2014)

forcePD

If TRUE the function checks if the correlation matrix is positive definite. If the matrix is not positive definite nearPD from the Matrix package will be used (Bates and Maechler, 2014).

missing

Corresponds to the missing argument in lavCor

verbose

Logical, should information be printed to the console?

Author

Sacha Epskamp <[e-mail]>

References

Yves Rosseel (2012). lavaan: An R Package for Structural Equation Modeling. Journal of Statistical Software, 48(2), 1-36. URL http://www.jstatsoft.org/v48/i02/.

Tuo Zhao, Han Liu, Kathryn Roeder, John Lafferty and Larry Wasserman (2014). huge: High-dimensional Undirected Graph Estimation. R package version 1.2.6. http://CRAN.R-project.org/package=huge

Douglas Bates and Martin Maechler (2014). Matrix: Sparse and Dense Matrix Classes and Methods. R package version 1.1-3. http://CRAN.R-project.org/package=Matrix

Examples

if (FALSE) {
### Examples from lavCor (lavaan): ###

library("lavaan")

# Holzinger and Swineford (1939) example
HS9 <- HolzingerSwineford1939[,c("x1","x2","x3","x4","x5",
                                 "x6","x7","x8","x9")]

# Pearson correlations
cor_auto(HS9)

# ordinal version, with three categories
HS9ord <- as.data.frame( lapply(HS9, cut, 3, labels=FALSE) )

# polychoric correlations, two-stage estimation
cor_auto(HS9ord)
}