omega.graph {psych} | R Documentation |

Hierarchical factor structures represent the correlations between variables in terms of a smaller set of correlated factors which themselves can be represented by a higher order factor.

Two alternative solutions to such structures are found by the `omega`

function. The correlated factors solutions represents the effect of the higher level, general factor, through its effect on the correlated factors. The other representation makes use of the Schmid Leiman transformation to find the direct effect of the general factor upon the original variables as well as the effect of orthogonal residual group factors upon the items.

Graphic presentations of these two alternatives are helpful in understanding the structure. omega.graph draws both such structures. Graphs are drawn directly onto the graphics window or expressed in ``dot" commands for conversion to graphics using implementations of Graphviz.

Using Graphviz allows the user to clean up the Rgraphviz output.

In addition

omega.graph(om.results, out.file = NULL, sl = TRUE, labels = NULL, size = c(8, 6), node.font = c("Helvetica", 14), edge.font = c("Helvetica", 10), rank.direction=c("RL","TB","LR","BT"), digits = 1, title = "Omega", ...)

`om.results` |
The output from the omega function |

`out.file` |
Optional output file for off line analysis using Graphviz |

`sl` |
Orthogonal clusters using the Schmid-Leiman transform (sl=TRUE) or oblique clusters |

`labels` |
variable labels |

`size` |
size of graphics window |

`node.font` |
What font to use for the items |

`edge.font` |
What font to use for the edge labels |

`rank.direction` |
Defaults to left to right |

`digits` |
Precision of labels |

`title` |
Figure title |

`...` |
Other options to pass into the graphics packages |

Requires the Rgraphviz package. omega requires the GPArotation package.

`clust.graph ` |
A graph object |

`sem` |
A matrix suitable to be run throughe the sem function in the sem package. |

Requires rgraphviz. – omega requires GPArotation

http://personality-project.org/revelle.html

Maintainer: William Revelle revelle@northwestern.edu

http://personality-project.org/r/r.omega.html

Revelle, W. (in preparation) An Introduction to Psychometric Theory with applications in R. http://personality-project.org/r/book

Revelle, W. (1979). Hierarchical cluster analysis and the internal structure of tests. Multivariate Behavioral Research, 14, 57-74. (http://personality-project.org/revelle/publications/iclust.pdf)

Zinbarg, R.E., Revelle, W., Yovel, I., & Li. W. (2005). Cronbach's Alpha, Revelle's Beta, McDonald's Omega: Their relations with each and two alternative conceptualizations of reliability. Psychometrika. 70, 123-133. http://personality-project.org/revelle/publications/zinbarg.revelle.pmet.05.pdf

Zinbarg, R., Yovel, I., Revelle, W. & McDonald, R. (2006). Estimating generalizability to a universe of indicators that all have one attribute in common: A comparison of estimators for omega. Applied Psychological Measurement, 30, 121-144. DOI: 10.1177/0146621605278814 http://apm.sagepub.com/cgi/reprint/30/2/121

`omega`

, `make.hierarchical`

, `ICLUST.rgraph`

#24 mental tests from Holzinger-Swineford-Harman if(require(GPArotation) ) {om24 <- omega(Harman74.cor$cov,4) } #run omega if(require(Rgraphviz) ){om24pn <- omega.graph(om24,sl=FALSE)} #show the structure # #example hierarchical structure from Jensen and Weng if(require(GPArotation) ) {jen.omega <- omega(make.hierarchical())} if(require(Rgraphviz) ) {om.jen <- omega.graph(jen.omega,sl=FALSE) }

[Package *psych* version 1.0-68 Index]