Role of ancillary variables in the design, analysis, and interpretation of animal experiments.
During the course of an experiment using animals, many variables (e.g., age, body weight at several times, food and water consumption, hematology, and clinical biochemistry) and other characteristics are often recorded in addition to the primary response variable(s) specified by the experimenter. These additional variables have an important role in the design and interpretation of the experiment. They may be formally incorporated into the design and/or analysis and thus increase precision and power. However, even if these variables are not incorporated into the primary statistical design or into the formal analysis of the experiment, they may nevertheless be used in an ancillary or exploratory way to provide valuable information about the experiment, as shown by various examples. Used in this way, ancillary variables may improve analysis and interpretation by providing an assessment of the randomization process and an approach to the identification of outliers, lead to the generation of new hypotheses, and increase generality of results or account for differences in results when compared across different experiments. Thus, appropriate use of additional variables may lead to reduction in the number of animals required to achieve the aims of the experiment and may provide additional scientific information as an extra benefit. Unfortunately, this type of information is sometimes effectively discarded because its potential value is not recognized. Guidelines for use of animals include, in addition to the obligation to follow humane procedures, the obligation to use no more animals than necessary. Ethical experimental practice thus requires that all information be properly used and reported.
Gaines Das
Rose E
RE
National Institute for Biological Standards and Control, Potters Bar, Herts, UK.
D000818:Animals; D000830:Animals, Laboratory; D003627:Data Interpretation, Statistical; D004305:Dose-Response Relationship, Drug; D015987:Effect Modifier, Epidemiologic; D015999:Multivariate Analysis; D011897:Random Allocation; D012107:Research Design / Q000592:standards*; D015262:Xenobiotics / Q000494:pharmacology
D015262:Xenobiotics