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Longitudinal models...
Longitudinal models of growth and survival applied to the early detection of Alzheimer's disease
- Article/chapterEnglish2005
Publisher, publication year, extent ...
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2016-06-29
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SAGE Publications,2005
Numbers
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LIBRIS-ID:oai:prod.swepub.kib.ki.se:1960341
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http://kipublications.ki.se/Default.aspx?queryparsed=id:1960341URI
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https://doi.org/10.1177/0891988705281879DOI
Supplementary language notes
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Language:English
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Summary in:English
Part of subdatabase
Classification
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Subject category:ref swepub-contenttype
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Subject category:art swepub-publicationtype
Notes
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This article explores new statistical methodologies for using longitudinal data in the early prediction of Alzheimer’s disease (AD). Specifically, the authors examine some new techniques that allow the joint or “shared” estimation of longitudinal components based on both duration (survival) and quantitative changes (growth curves). These new shared growth-survival parameter models may be used to characterize the declining functions that anticipate the onset of AD. The authors apply these models to data from the Kungsholmen Project, a longitudinal study of aging in Stockholm, Sweden. They examine age-based survival-frailty models for the onset of AD, latent growth-decline curve models for changes in cognition over age, and 3 alternative forms of models for the shared relationships of survival and early cognitive decline. The accuracy and reliability of this approach is considered for a better understanding of the developmental course of AD in these data, including the potential removal of biases due to subject selection.
Added entries (persons, corporate bodies, meetings, titles ...)
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Small, BJ
(author)
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Backman, LKarolinska Institutet
(author)
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Fratiglioni, LKarolinska Institutet
(author)
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Karolinska Institutet
(creator_code:org_t)
Related titles
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In:Journal of geriatric psychiatry and neurology: SAGE Publications18:4, s. 234-2410891-98871552-5708
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