Data from: On the comparison of the strength of morphological integration across morphometric datasets

Evolutionary morphologists frequently wish to understand the extent to
which organisms are integrated, and whether the strength of morphological
integration among subsets of phenotypic variables differ among taxa or
other groups. However, comparisons of the strength of integration across
datasets are difficult, in part because the summary measures that
characterize these patterns (RV and rPLS) are dependent both on sample
size and on the number of variables. As a solution to this issue we
propose a standardized test statistic (a z-score) for measuring the degree
of morphological integration between sets of variables. The approach is
based on a partial least squares analysis of trait covariation, and its
permutation-based sampling distribution. Under the null hypothesis of a
random association of variables, the method displays a constant expected
value and confidence intervals for datasets of differing sample sizes and
variable number, thereby providing a consistent measure of integration
suitable for comparisons across datasets. A two-sample test is also
proposed to statistically determine whether levels of integration differ
between datasets, and an empirical example examining cranial shape
integration in Mediterranean wall lizards illustrates its use. Some
extensions of the procedure are also discussed.