Battery reduction is used to select a subset of m variables from an original set of n variables (m < n) that reproduce a large proportion of the variance in the original set of n variables. There are a number of procedures for performing battery reduction analysis. A popular method involves first performing a principal components analysis to select m components, which account for the salient variance in the original data. Gram–Schmidt orthogonal rotations are then performed to determine the m variables that account for the largest proportion of variance. The procedure is illustrated and reference made to a SAS macro for performing the analysis.