Methodology for the generation of normative data for the U.S. adult Spanish-speaking population: a Bayesian approach

Objective: To present the methodology for a study generating normative neuropsychological test data for healthy Spanish-speaking adults (18-80 years old) living in the U.S. using Bayesian inference as a novel approach. Method: The study sample consisted of 253 healthy adults from eight U.S. regions (California, Connecticut, Florida, Indiana, New Jersey, Oregon, Virginia, and Wisconsin), with individuals originating from a diverse array of Latin American countries. To participate in the study, individuals must have met the following criteria: were between 18 and 80 years of age, had lived in the U.S. for at least 1 year (12 continuous months), self-identified Spanish as their dominant language, had at least one year of formal education, were able to read and write in Spanish at the time of evaluation, scored ¿23 on the Mini-Mental State Examination, scored <10 on the Patient Health Questionnaire¿9, and scored <10 on the Generalized Anxiety Disorder scale. Participants completed 12 neuropsychological tests. Reliability statistics and norms were calculated for all tests. Conclusions: This was the first normative study for Spanish-speaking adults in the U.S. to implement demographic, acculturation, and bilingual dominance measures as possible controls. Additionally, it was the first study to use Bayesian linear or generalized linear regression models for generating normative data in neuropsychology.