How Many do we Need? Sample Size Requirements for Continuous Norms

Precise norm scores are essential for psychological diagnostics. While conventional norming estimates norms based on subgroups, continuous norming uses regression to estimate norms based on the entire sample. One consequence of this is that continuous norming achieves a comparable precision with smaller sample sizes compared to conventional norming. However, clear guidelines on the required sample sizes for continuous norming are scarce. To provide empirically based guidance for determining required sample sizes in normative studies using continuous norming, we used normative data from two intelligence tests to evaluate the precision of continuous norms across various sample sizes, norm predictor values, and latent trait levels. Results show that continuous norms can achieve similar precision as conventional norms with substantially smaller samples (N = 1,000–1,500 vs. N = 2,500–3,000). However, precision declines at extreme percentiles and norm predictor values, emphasizing the need to tailor sample size planning to the specific test.