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Measuring self-complexity: A critical analysis of Linville's H statistic
Citation
Luo, W., Watkins, D., & Lam, R. Y. H. (2008). Measuring self-complexity: A critical analysis of Linville's H statistic. Journal of Applied Measurement, 9(4), 357-373.
Author
Luo, Serena Wenshu
•
Watkins, David
•
Lam, Raymond Y. H.
Abstract
The paper argues that the most commonly used measure of self-complexity, Linville’s H statistic, cannot measure this construct appropriately. It first examines the mathematical properties of H and its relationships with five related indices: the number of self-aspects, the overlap among self-aspects, the average inter-aspect correlation, the ratio of endorsement, and the HICLAS attribute class number. Then, a demonstration study using simulations is reported. Three conclusions are drawn. H and the HICLAS attribute class number are similar in the way they are calculated. Both indices are highly related to the number of self-aspects, while their relationship to overlap is not monotonic. Overlap is affected by the ratio of endorsement and the average inter-aspect correlation but cannot represent the notion of redundancy among traits which directly determines Linville’s H statistic. These conclusions are employed to explain the inconsistent findings relating self-complexity and adaptation and an alternative measurement approach is proposed.
Publisher
JAM Press
Journal
Journal of Applied Measurement