Literature DB >> 21038965

Latent structure and factorial invariance of a neuropsychological test battery for the study of preclinical Alzheimer's disease.

N Maritza Dowling1, Bruce Hermann1, Asenath La Rue1, Mark A Sager1.   

Abstract

OBJECTIVE: To examine the latent structure of a test battery currently being used in a longitudinal study of asymptomatic middle-aged adults with a parental history of Alzheimer's disease (AD) and test the invariance of the factor solution across subgroups defined by selected demographic variables and known genetic risk factors for AD.
METHOD: An exploratory factor analysis (EFA) and a sequence of confirmatory factor analyses (CFA) were conducted on 24 neuropsychological measures selected to provide a comprehensive estimate of cognitive abilities most likely to be affected in preclinical AD. Once the underlying latent model was defined and the structural validity established through model comparisons, a multigroup confirmatory factor analysis model was used to test for factorial invariance across groups.
RESULTS: The EFA solution revealed a factor structure consisting of five constructs: verbal ability, visuospatial ability, speed & executive function, working memory, and verbal learning & memory. The CFA models provided support for the hypothesized 5-factor structure. Results indicated factorial invariance of the model across all groups examined.
CONCLUSIONS: Collectively, the results suggested a relatively strong psychometric basis for using the factor structure in clinical samples that match the characteristics of this cohort. This confirmed an invariant factor structure should prove useful in research aimed to detect the earliest cognitive signature of preclinical AD in similar middle aged cohorts. (c) 2010 APA, all rights reserved

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Year:  2010        PMID: 21038965      PMCID: PMC3057903          DOI: 10.1037/a0020176

Source DB:  PubMed          Journal:  Neuropsychology        ISSN: 0894-4105            Impact factor:   3.295


  34 in total

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5.  Examining Population Differences in Within-Person Variability in Longitudinal Designs Using Latent Variable Modeling: An Application to the Study of Cognitive Functioning of Older Adults.

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