The impact of leverage, influential observations, and multicollinearity in mixture experiments is discussed. By example, it is shown that consideration of these factors is important in the practical selection of a mixture design. Both standard simplex-type mixture designs and computer-generated designs for constrained hyperpolyhedron regions can have very non-uniform distributions of leverage, and consequently, some design points may exert disproportionate influence on the least squares fit. Generally, multicollinearity is not a serious problem in simplex-type designs, provided that when constraints are present the pseudocomponent transformation is used. However, in computer-generated designs, high levels of multicollinearity may be present. How these potential problems can be evaluated and considered in selecting a mixture design is illustrated.