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P1‐550: REFINING A LATENT DEMENTIA INDICATOR FOR A MULTI‐STUDY CONSORTIUM
Author(s) -
Luczak Susan E.,
Beam Christopher R.,
Reynolds Chandra A.,
Panizzon Matthew S.,
Gatz Margaret
Publication year - 2019
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1016/j.jalz.2019.06.1155
Subject(s) - dementia , twin study , medical diagnosis , cognition , confirmatory factor analysis , cognitive test , psychology , bivariate analysis , correlation , clinical psychology , medicine , structural equation modeling , psychiatry , statistics , disease , mathematics , pathology , heritability , biology , genetics , geometry
v A variety of dementia indicators have been proposed when clinical diagnoses are unavailable, ranging from cutoff scores on a cognitive screening measure such as MMSE to weighted combinations of cognitive test scores. v Latent variable dementia indicators, “delta” (δ), are reliable predictors of dementia risk (Gavett et al., Peh et al., Royall & Palmer). δ reflects variance in a set of cognitive and functional ability indicators beyond variance accounted for by a general intelligence factor (g’) solely indicated by cognitive scores. δ is a continuous measure of liability to dementia. v We built on this δ approach utilizing samples from the Interplay of Genes and Environment in Multiple Studies (IGEMS) consortium. Instead of creating a separate latent construct of g’, we correlated the residuals of cognitive items that are indicative of cognitive ability. We also included memory and functional ability as indicators of δ. v We first examined samples where clinical diagnoses were available to test the validity of δ. We then applied this approach with a sample where clinical diagnoses were not available.