Open AccessNormative data from linear and nonlinear quantile regression in CANTAB: Cognition in mid‐to‐late life in an epidemiological sample
Author(s) -
Abbott Rosemary A.,
Skirrow Caroline,
Jokisch Martha,
Timmers Maarten,
Streffer Johannes,
Nueten Luc,
Krams Michael,
Winkler Angela,
Pundt Noreen,
Nathan Pradeep J.,
Rock Philippa,
Cormack Francesca K.,
Weimar Christian
Publication year - 2019
Publication title -
alzheimer's and dementia: diagnosis, assessment and disease monitoring
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.497
H-Index - 37
ISSN - 2352-8729
DOI - 10.1016/j.dadm.2018.10.007
Subject(s) - quantile regression , normative , psychology , neuropsychology , cognition , quantile , episodic memory , linear regression , neuropsychological test , regression , developmental psychology , econometrics , statistics , mathematics , psychiatry , philosophy , epistemology , psychoanalysis
Normative cognitive data can help to distinguish pathological decline from normal aging. This study presents normative data from the Cambridge Neuropsychological Test Automated Battery, using linear regression and nonlinear quantile regression approaches. Methods Heinz Nixdorf Recall study participants completed Cambridge Neuropsychological Test Automated Battery tests: paired‐associate learning, spatial working memory, and reaction time. Data were available for 1349‐1529 healthy adults aged 57‐84 years. Linear and nonlinear quantile regression analyses examined age‐related changes, adjusting for sex and education. Quantile regression differentiated seven performance bands (percentiles: 97.7, 93.3, 84.1, 50, 15.9, 6.7, and 2.3). Results Normative data show age‐related cognitive decline across all tests, but with quantile regression revealing heterogeneous trajectories of cognitive aging, particularly for the test of episodic memory function (paired‐associate learning). Discussion This study presents normative data from Cambridge Neuropsychological Test Automated Battery in mid‐to‐late life. Quantile regression can model heterogeneity in age‐related cognitive trajectories as seen in the paired‐associate learning episodic memory measure.