Automated procedure for demographic adjustments on cognitive test scores

Performances of normal people on cognitive tests are known to vary by demographic characteristics, such as age, education, and sex. Thus, cognitive test scores should be corrected for demographic influences when they are used to detect below-expected results due to disease or injury involving the central nervous system (CNS). Normative corrections, if estimated from a large, diverse, and well-characterized cohort of controls, help to remove expected differences in cognitive performance associated with normal demographic characteristics and associated socio-economic disadvantages. In this paper, we (1) describe in detail the process of generating regression-based normative standards, and its advantages and limitations, (2) provide recommendations for applying these normative standards to data from individuals and populations at risk for CNS dysfunction, and (3) introduce an R package, test2norm, that contains functions for producing and applying normative formulas to generate demographically corrected scores for measuring deviations from expected, normal cognitive performances.