title: Rotational distortion in conventional allometric analyses.
abstract: Three data sets from the recent literature were submitted to new analyses to illustrate the rotational distortion that commonly accompanies traditional allometric analyses and that often causes allometric equations to be inaccurate and misleading. The first investigation focused on the scaling of evaporative water loss to body mass in passerine birds; the second was concerned with the influence of body size on field metabolic rates of rodents; and the third addressed interspecific variation in kidney mass among primates. Straight lines were fitted to logarithmic transformations by Ordinary Least Squares and Generalized Linear Models, and the resulting equations then were re-expressed as two-parameter power functions in the original arithmetic scales. The re-expressed models were displayed on bivariate graphs together with tracings for equations fitted directly to untransformed data by nonlinear regression. In all instances, models estimated by back-transformation failed to describe major features of the arithmetic distribution whereas equations fitted by nonlinear regression performed quite well. The poor performance of equations based on models fitted to logarithms can be traced to the increased weight and leverage exerted in those analyses by observations for small species and to the decreased weight and leverage exerted by large ones. The problem of rotational distortion can be avoided by performing exploratory analysis on untransformed values and by validating fitted models in the scale of measurement.
authors.affiliation: Department of Biology, Colorado State University, Fort Collins, CO 80523-1878, USA. Gary.Packard@ColoState.edu
authors.forename: Gary C
authors.initials: GC
authors.lastname: Packard
mesh_terms: D000818:Animals; D001481:Basal Metabolism / Q000502:physiology; D001717:Birds; D049628:Body Size / Q000502:physiology*; D003625:Data Collection; D003627:Data Interpretation, Statistical; D004734:Energy Metabolism / Q000502:physiology; D007668:Kidney / Q000378:metabolism*; D016014:Linear Models; D008954:Models, Biological; D017711:Nonlinear Dynamics; D009929:Organ Size; D011323:Primates; D012044:Regression Analysis; D012377:Rodentia; D014870:Water Loss, Insensible / Q000502:physiology*