Utility of inferential norming with smaller sample sizes

We examined the utility of inferential norming using small samples drawn from the larger Wechsler Intelligence Scales for Children-Fourth Edition (WISC-IV) standardization data set. The quality of the norms was estimated with multiple indexes such as polynomial curve fit, percentage of cases receiving the same score, average absolute score differences, score distributions, score correlations, and sensitivity in identifying children who are gifted or intellectually disabled. Norms developed using inferential norming method and sample sizes of 50 and 75 per age group had qualities comparable to the norms derived using larger sample size. So, when large sample sizes are infeasible due to practical constraints, N = 50 per group can be considered a lower bound to derive decent norms using inferential norming method. Cautions for implementing inferential norming with smaller sample sizes and suggestions for future research are discussed.