Environmental and Ecological Statistics 11, 55-71, 2004 Corrected version of manuscript, prepared by the authors. Random denominators and the analysis of ratio data MARTIN LIERMANN,1* ASHLEY STEEL, 1 MICHAEL ROSING2 and PETER GUTTORP3 1Watershed Program, NW Fisheries Science Center, 2725 Montlake Blvd. East, Seattle, WA 98112 E-mail:
[email protected] 2Greenland Institute of Natural Resources 3National Research Center for Statistics and the Environment, Box 354323, University of Washington, Seattle, WA 98195 Ratio data, observations in which one random value is divided by another random value, present unique analytical challenges. The best statistical technique varies depending on the unit on which the inference is based. We present three environmental case studies where ratios are used to compare two groups, and we provide three parametric models from which to simulate ratio data. The models describe situations in which (1) the numerator variance and mean are proportional to the denominator, (2) the numerator mean is proportional to the denominator but its variance is proportional to a quadratic function of the denominator and (3) the numerator and denominator are independent. We compared standard approaches for drawing inference about differences between two distributions of ratios: t-tests, t-tests with transformations, permutation tests, the Wilcoxon rank test, and ANCOVA-based tests. Comparisons between tests were based both on achieving the specified alpha-level and on statistical power. The tests performed comparably with a few notable exceptions. We developed simple guidelines for choosing a test based on the unit of inference and relationship between the numerator and denominator. Keywords: ANCOVA, catch per-unit effort, fish density, indices, per-capita, per-unit, randomization tests, t-tests, waste composition 1352-8505 © 2004 Kluwer Academic Publishers 1.