Short-Cut Multiple Comparisons for Balanced Single and Double Classifications: Part 1, Results

Abstract

Methods are provided for the rapid analysis of data in balanced single and double classifications. Sums of ranges provide short-cut measures of variability with only slight loss of efficiency. Tables of factors are provided to convert these sums directly into widths of simultaneous confidence intervals for simple comparisons of group totals. Two illustrative examples are treated in detail. The proposed procedures are recommended for routine use in initial analyses, though not to the exclusion of more refined procedures. The paper includes a general discussion of multiple comparison procedures: when they should and should not be used, the importance of confidence procedures and their advantages over significance procedures, choice among multiple comparisons confidence procedures, choice and description of error rates. It does not attempt to compare multiple comparison and multiple decision procedures.