Learn R Programming

psych (version 1.0-77)

fa.graph: Graph factor loading matrices

Description

Factor analysis or principal components analysis results are typically interpreted in terms of the major loadings on each factor. These structures may be represented as a table of loadings or graphically, where all loadings with an absolute value > some cut point are represented as an edge (path).

Usage

fa.graph(fa.results, out.file = NULL, labels = NULL, cut = 0.3, simple = TRUE, size = c(8, 6), node.font = c("Helvetica", 14), edge.font = c("Helvetica", 10),  rank.direction=c("RL","TB","LR","BT"), digits = 1, main = "Factor Analysis", ...)

Arguments

fa.results
The output of factor analysis or principal components analysis
out.file
If it exists, a dot representation of the graph will be stored here
labels
Variable labels
cut
Loadings with abs(loading) > cut will be shown
simple
Only the biggest loading per item is shown
size
graph size
node.font
edge.font
rank.direction
digits
Number of digits to show as an edgelable
main
Graphic title
...
other parameters

Value

  • A graph is drawn using rgraphviz. If an output file is specified, the graph instructions are also saved in the dot language.

Details

Path diagram representations have become standard in confirmatory factor analysis, but are not yet common in exploratory factor analysis. Representing factor structures graphically helps some people understand the structure.

Although a nice graph is drawn for the orthogonal factor case, the oblique factor drawing is acceptable, but is better if cleaned up outside of R.

See Also

omega.graph, ICLUST.graph

Examples

Run this code
test.simple <- factor.pa(item.sim(16),2)
if(require(Rgraphviz)) {fa.graph(test.simple) }

Run the code above in your browser using DataLab