Tableplot: A New Tool for Assessing Precise Predictions

DOI 10.1027/0044-3409.217.1.38 Abstract. In the debate over null hypothesis significance testing, Paul Meehl strongly advocated appraising theories through the generation and evaluation of precise predictions (e.g., Meehl, 1978). The study of personality structure through the five-factor model (FFM; McCrae & John, 1992) is an important area of research where one encounters many precise predictions. Extant methods of assessing such predictions, however, do not allow researchers to examine the outcome of the predictions in great detail. That is, it may be difficult to determine how estimates fail to match predicted values. As Meehl argued, one must examine how a theory fails to predict in order to refine and improve the theory. To promote better theory appraisal in FFM research, we present a powerful new tool, called a tableplot (Kwan, 2008a), that can summarize and clarify factor-analytic results. Specifically, we illustrate how the tableplot enables detailed appraisal of precise predictions in the FFM.