The Scale of Accurate Personality Prediction (SAPP): Predicting Low, Medium, or High SAPP Scores from the 16PF Primary and Global Factors
Date of Award
Doctoral Research Project
Doctor of Psychology (PsyD)
Richard T. Elmore Jr.
Lisa A. Steelman
To measure a person’s self-knowledge, Miller (2000) created the Scale of Accurate Personality Prediction (SAPP), a measure derived by comparing subjects’ obtained and self-predicted scores across the 21 scales of the Sixteen Personality Factor Questionnaire (16PF). Most recently, DiLullo (2018) assessed which of the 21 16PF primary and global factors would best predict subjects’ SAPP scores, allowing for the derivation of SAPP scores directly from the existing 16PF factors. Due to the significant variability found across the results in DiLullo’s study, this study adjusted the methodology to encourage greater consistency across samples. To do so, categorical SAPP scores were utilized instead of continuous SAPP scores. Therefore, each respondent’s SAPP score was first converted to a categorized score of either low (STEN scores of 1-4), medium (STEN scores of 5 or 6), or high (STEN scores of 7-10). Then, a series of multinomial logistic regression analyses were conducted across the total sample and two odd/even samples drawn from an archival database of 688 participants. What resulted was that in all three of the samples, Emotional Stability (C+), Tough-Mindedness (TM-), and Tension (Q4+) emerged as the strongest predictors of self-knowledge, while Vigilance (L-) appeared as an additional predictor in two of the three samples. The consistency amongst the samples’ results suggests that a subject’s level of self-knowledge is able to be identified from the existing 16PF scales, and more specifically, from the aforementioned four factors.
Reeder, Cayleigh Katherine, "The Scale of Accurate Personality Prediction (SAPP): Predicting Low, Medium, or High SAPP Scores from the 16PF Primary and Global Factors" (2020). Theses and Dissertations. 336.
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