  We present an analysis of eight measures used for quantifying morphological
complexity of natural languages. The measures we study are corpus-based
measures of morphological complexity with varying requirements for corpus
annotation. We present similarities and differences between these measures
visually and through correlation analyses, as well as their relation to the
relevant typological variables. Our analysis focuses on whether these
`measures' are measures of the same underlying variable, or whether they
measure more than one dimension of morphological complexity. The principal
component analysis indicates that the first principal component explains 92.62
% of the variation in eight measures, indicating a strong linear dependence
between the complexity measures studied.
