Improved Statistical Design

Anyone who has ever taken a course in experimental design or applied statistics has been bombarded with the importance of consulting with a statistician during the design phase of the experiment and not when the data collected needs to be analyzed.  Improper design of experimental protocols and/or the failure to use appropriate statistical methods can result in the usage of an inappropriate number of experimental animals.  A variety of design strategies are available which can reduce the number of animals needed in a given study. Experimental protocols which utilize serial sacrifice, group sequential testing and crossover designs can significantly reduce the numbers of animals required.  The availability of low cost statistical packages  permits investigators access to sophisticated data  management and analysis.  This accessibility makes possible the use of design criteria and complicated statistical analysis which previously have been confined to institutions with large statistical support units. With this ability at their finger tips, investigators should be able to maximize the analysis of the data generated from each animal used, thus reducing the total numbers of animals necessary for a particular set of data.

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