The degree of nonorthogonality in a factorial design was systematically increased. Five methods of dealing with nonorthogonality were selected and applied: two were least squares solutions (Method 1 and Method 2); two were approximate solutions (the unweighted means analysis and the method of expected frequencies); and the fifth was the alternative of data elimination. Under extreme nonorthogonality all methods converged in yielding conclusions which while erroneous were similar across methods. Under moderate nonorthogonality, however, the unweighted means analysis and Method 1 were superior. Overall, the data elimination alternaitive was inferior in that it led to more type 2 errors than any of the other four methods. (Author)