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Shows that correlations between theoretical predictions and data can be higher for incorrect than for correct models by analyses of 2 sets of hypothetical data. This fact raises questions about the conclusions of recent studies that use correlation as an index of fit. It is proposed that functional measurement provides a sounder basis for model evaluation by placing scaling in the context of model fitting and by testing deviations from prediction rather than concentrating on overall goodness of fit.
Psychological Bulletin – American Psychological Association
Published: Apr 1, 1973
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