psych (version 2.1.9)

VSS.plot: Plot VSS fits


The Very Simple Structure criterion ( VSS) for estimating the optimal number of factors is plotted as a function of the increasing complexity and increasing number of factors.


VSS.plot(x, title = "Very Simple Structure", line = FALSE)



output from VSS


any title


connect different complexities


A plot window showing the VSS criterion varying as the number of factors and the complexity of the items.


Item-factor models differ in their "complexity". Complexity 1 means that all except the greatest (absolute) loading for an item are ignored. Basically a cluster model (e.g., ICLUST). Complexity 2 implies all except the greatest two, etc.

Different complexities can suggest different number of optimal number of factors to extract. For personality items, complexity 1 and 2 are probably the most meaningful.

The Very Simple Structure criterion will tend to peak at the number of factors that are most interpretable for a given level of complexity. Note that some problems, the most interpretable number of factors will differ as a function of complexity. For instance, when doing the Harman 24 psychological variable problems, an unrotated solution of complexity one suggests one factor (g), while a complexity two solution suggests that a four factor solution is most appropriate. This latter probably reflects a bi-factor structure.

For examples of VSS.plot output, see


See Also

VSS, ICLUST, omega


Run this code
# NOT RUN { <- Harman74.cor$cov
my.vss <- VSS(         #suggests that 4 factor complexity two solution is optimal
VSS.plot(my.vss,title="VSS of Holzinger-Harmon problem")                 #see the graphics window

# }

Run the code above in your browser using DataLab