Strengths and limitations of ipsative measurement
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The relative merits of ipsative measurement for multi-scale psychometric instruments are discussed. Standard psychometric analyses are found to be inappropriate with small numbers of scales, or sets of scales with strong positive intercorrelations. However, for larger sets of scales (N ∼ 30) with low average intercorrelations, ipsative data seems to provide robust statistical results in reliability analyses but not under factor analysis. It is argued that the potential of forced-choice formats to control for some of the response biases typical of normative scales means that they could have substantial advantages while data from score distributions are used to show that for higher numbers of scales, the vast majority of profiles are not so skewed that they would be likely to be distorted by a forced-choice response format. The implications for score interpretation are discussed.