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lavaan (version 0.6-19)

summary.efaList: Summarizing EFA Fits

Description

S3 summary and print methods for class efaList.

Usage

# S3 method for efaList
summary(object,
        nd = 3L, cutoff = 0.3, dot.cutoff = 0.1, alpha.level = 0.01,
        lambda = TRUE, theta = TRUE, psi = TRUE, fit.table = TRUE,
        fs.determinacy = FALSE, eigenvalues = TRUE, sumsq.table = TRUE, 
        lambda.structure = FALSE, se = FALSE, zstat = FALSE,
        pvalue = FALSE, ...)

# S3 method for efaList.summary print(x, nd = 3L, cutoff = 0.3, dot.cutoff = 0.1, alpha.level = 0.01, ...)

Value

The function summary.efaList computes and returns a list of summary statistics for the list of EFA models in object.

Arguments

object

An object of class efaList, usually, a result of a call to efa with (the default) output = "efa".

x

An object of class summary.efaList, usually, a result of a call to summary.efaList.

nd

Integer. The number of digits that are printed after the decimal point in the output.

cutoff

Numeric. Factor loadings smaller that this value (in absolute value) are not printed (even if they are significantly different from zero). The idea is that only medium to large factor loadings are printed, to better see the overall structure.

dot.cutoff

Numeric. Factor loadings larger (in absolute value) than this value, but smaller (in absolute value) than the cutoff value are shown as a dot. They represent small loadings that may still need your attention.

alpha.level

Numeric. If the the p-value of a factor loading is smaller than this value, a significance star is printed to the right of the factor loading. To switch this off, use alpha.level = 0.

lambda

Logical. If TRUE, include the (standardized) factor loadings in the summary.

theta

Logical. If TRUE, include the unique variances and the communalities in the table of factor loadings.

psi

Logical. If TRUE, include the factor correlations in the summary. Ignored if only a single factor is used.

fit.table

Logical. If TRUE, show fit information for each model.

fs.determinacy

Logical. If TRUE, show the factor score determinacy values per factor (assuming regression factor scores are used) and their squared values.

eigenvalues

Logical. If TRUE, include the eigenvalues of the sample variance-covariance matrix in the summary.

sumsq.table

Logical. If TRUE, include a table including sums of squares of factor loadings (and related measures) in the summary. The sums of squares are computed as the diagonal elements of Lambda times Psi (where Psi is the matrix of factor correlations.). If orthogonal rotation was used, Psi is diagonal and the sums of squares are identical to the sums of the squared column elements of the Lambda matrix (i.e., the factor loadings). This is no longer the case when obique rotation has been used. But in both cases (orthgonal or oblique), the (total) sum of the sums of squares equals the sum of the communalities. In the second row of the table (Proportion of total), the sums of squares are divided by the total. In the third row of the table (Proportion var), the sums of squares are divided by the number of items.

lambda.structure

Logical. If TRUE, show the structure matrix (i.e., the factor loadings multiplied by the factor correlations).

se

Logical. If TRUE, include the standard errors of the standardized lambda, theta and psi elements in the summary.

zstat

Logical. If TRUE, include the Z-statistics of the standardized lambda, theta and psi elements in the summary.

pvalue

Logical. If TRUE, include the P-values of the standardized lambda, theta and psi elements in the summary.

...

Further arguments passed to or from other methods.

Examples

Run this code
## The famous Holzinger and Swineford (1939) example
fit <- efa(data = HolzingerSwineford1939, 
           ov.names = paste("x", 1:9, sep = ""),
           nfactors = 1:3,
           rotation = "geomin",
           rotation.args = list(geomin.epsilon = 0.01, rstarts = 1))
summary(fit, nd = 3L, cutoff = 0.2, dot.cutoff = 0.05,
        lambda.structure = TRUE, pvalue = TRUE)

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