ABSTRACT
Analysis of variance, also known as ANOVA, is perhaps the most powerful statistical tool. ANOVA is a general method of analyzing data from designed experiments, whose objective is to compare two or more group means. The t test is a special case of ANOVA in which only two means are compared. By designed experiments, we mean experiments with a particular structure. Well-designed experiments are usually optimal with respect to meeting study objectives. The statistical analysis depends on the design, and the discussion of ANOVA therefore includes common statistical designs used in pharmaceutical research. Analysis of variance designs can be more or less complex. The designs can be very simple, as in the case of the t-test procedures presented in Chapter 5. Other designs can be quite complex, sometimes depending on computers for their solution and analysis. As a rule of thumb, one should use the simplest design that will achieve the experimental objectives. This is particularly applicable to experiments otherwise difficult to implement, such as is the case in clinical trials.
