Generally, multivariate population covariance matrices for measurements xi of parts of organisms will be of the form X = W + A, with W resulting from systematic covariance and A from independent random variance of individual xi . For isometry or allometry (constant equal or differential relative growth or size) W for log x must be of rank one. Then if also the random variance of log x is uniform for all i the vectors of W will be vectors of X and the first principal vector of an observed covariance matrix S will provide an estimate of the underlying population relative growth or size pattern. Alternatively, if the random variance of each log xi is proportional to its systematic variance, the main diagonal elements of A, also estimable from S, will be proportional to those of W and hence when the latter is of rank one to the squares of its vector coefficients. Otherwise allometric coefficients must generally be estimated from factor analysis of S after screening of any variates whose relative growth is size-dependent. Tests of goodness of fit of allometric relations may be affected by non-normality of logarithmic size distributions. From an application of these considerations to illustrative data for nine body parts of rats it was inferred that in this instance liver, heart, spleen, lungs, skin and adrenal weights were consistent with a single allometric pattern, but that interrelations involving kidneys, genitals and brain were size-dependent.