Analysis of covariance: an alternative to nutritional indices

Some statistical problems are added to the growing list of cautionary tales regarding the use of the conventional, ratio-based nutritional indices (RCR, RGR, ECI, AD and ECD). Analysis of ratios is based on the, probably unrealistic, assumption of an isometric relationship between denominator and numerator variables. Analysis of covariance (ANCOVA) makes less restrictive assumptions, and additionally provides important information about the data which is lost by using ratio variables. We demonstrate, using computer-generated data sets, some of the pitfalls of statistical analysis of ratios and illustrate how these may be avoided using ANCOVA. Some possible consequences of such statistical iniquities for biological interpretations are discussed.