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In this article, autoregressive models and growth curve models are compared. Autoregressive models are useful because they allow for random change, permit scores to increase or decrease, and do not require strong assumptions about the level of measurement. Three previously presented designs for estimating stability are described: (a) time-series, (b)(More)
In accordance with the usual strategy of parsimony in science, the effects of extreme contexts upon absolute judgment were interpreted initially as illustrating a single process of rela-tivity of judgment or adaptation level. The most economical interpretation of the data to be presented here necessitates the postulation of two such processes, both(More)
When traits are measured by the same method (or at the same time) the intertrait correlations are higher than when the intertrait correlation is across methods. An empirical investigation of the nature of such method factors is reported, in which the method factors seem to operate in a multiplicative rather than additive way, or in which larger method(More)