Abstract

The value of personality test norms for use in work settings depends on norm sample size (N) and relevance, yet research on these criteria is scant and corresponding standards are vague. Using basic statistical principles and Hogan Personality Inventory (HPI) data from 5 sales and 4 trucking samples (N range=394–6,200), we show that (a) N>100 has little practical impact on the reliability of norm‐based standard scores (max=±10 percentile points in 99% of samples) and (b) personality profiles vary more from using different norm samples, between as well as within job families. Averaging across scales, T‐scores based on sales versus trucking norms differed by 7.3 points, whereas maximum differences averaged 7.4 and 7.5 points within the sets of sales and trucking norms, respectively, corresponding in each case to approximately ±14 percentile points. Slightly weaker results obtained using nine additional samples from clerical, managerial, and financial job families, and regression analysis applied to the 18 samples revealed demographic effects on four scale means independently of job family. Personality test developers are urged to build norms for more diverse populations, and test users, to develop local norms to promote more meaningful interpretations of personality test scores.

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