Norm-referenced assessments are critical for understanding an individual’s performance relative to similar-age peers. This information offers valuable context for screening, diagnostic evaluations, and progress monitoring. For example, we can recognize when a lack of a particular skill becomes a deficit based on when the majority of the population typically acquires it.
But how we develop those norms is important. Norms need to reliably reflect the population they represent, as the assessments that incorporate them rely on accuracy for precise interpretation. Traditional norming approaches divide participants into discrete age groups, though development doesn’t always fit neatly into age-based categories. For example, a child who just turned six isn’t necessarily developmentally different from a child who is 5 years and 11 months old, yet traditional norming methods may place them in different age groups.
In a recently published study, my colleagues and I examined whether continuous norming, which models age as a continuous variable rather than placing individuals into discrete age groups, could provide a more precise approach to developing norms for neurobehavioral assessments.
We compared traditional and continuous norming approaches across a wide range of simulated conditions, including different sample sizes. One continuous-norming approach, generalized additive models for location, scale, and shape (GAMLSS), consistently performed well, even with relatively small samples.
These findings suggest that continuous norming may offer a more precise and flexible approach to developing norms for neurobehavioral assessments. This matters for behavioral intervention because baseline and ongoing assessments need to identify areas that are outside of neurotypical development and, therefore, would benefit from intervention. Our norming approach allows for more accurate detection of these domains, enabling clinicians to identify appropriate treatment targets and supporting treatment authorization requests.
These findings suggest that continuous norming may offer a more precise and flexible approach to developing norms for neurobehavioral assessments. This matters for behavioral intervention because baseline and ongoing assessments need to identify areas that are outside of neurotypical development and, therefore, would benefit from intervention. Our norming approach allows for more accurate detection of these domains, enabling clinicians to identify appropriate treatment targets and supporting treatment authorization requests.
I invite you to read the full paper, Comparing traditional and continuous norming models for neurobehavioral assessments: A simulation study, to learn more about the methods we evaluated and what these findings may mean for the future of neurobehavioral assessment development.
Posted in Review
Comparing traditional and continuous norming models for neurobehavioral assessments: A simulation study
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