The statistical treatment of condition used in many previous studies has been to determine a predicted weight for a fish, and to calculate a ratio of actual to predicted weight. The ratios obtained, known as condition factor K, are then further analysed using analysis of variance or other techniques to relate changes in K to other independent variables. It is suggested that condition can be studied better by using a single model to analyse the response of fish weight to a number of factors simultaneously. This approach affords benefit from the simplicity of using an integrated analysis and avoids problems with skewed distributions of ratios. An example using data on the Pacific sardine, Sardinops sagax (Jenyns), is given. Changes in condition of this fish due to monthly, yearly and temperature effects are calculated. Copyright © 1992, Wiley Blackwell. All rights reserved