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P1‐462: A LATENT TRANSITION ANALYSIS MODEL TO ASSESS CHANGE IN COGNITIVE STATES AND PREDICT INCIDENT DEMENTIA: RESULTS FROM THE RUSH MEMORY AND AGING PROJECT
Author(s) -
Zammit Andrea R.,
Terrera Graciela Muniz,
Hall Charles B.,
Katz Mindy J.,
Bennett David A.,
Ezzati Ali,
Lipton Richard B.
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.2019.06.1067
Subject(s) - dementia , latent class model , psychology , neuropsychology , covariate , cognition , cognitive decline , gerontology , measurement invariance , cognitive impairment , audiology , medicine , statistics , confirmatory factor analysis , structural equation modeling , psychiatry , disease , mathematics
DIC was the third model. With the third model, we obtain graphs of probability of having dysexecutive syndrome according to the patient’s response time in each item. Five patients have a high probability of having dementia according to the model. Conclusions: Improving the equations including return variables increases the qualities of the statistical model. The predictive ability of the item response theory and the Bayesian theory for the early detection of dementia should be further studied.