The Scale of Accurate Personality Prediction (SAPP): Predicting Low, Medium, or High SAPP Scores from the 16PF Primary and Global Factors
Abstract
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.