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Imputation of missing longitudinal fMRI data
Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.ORCID iD: 0000-0003-1524-0851
Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Department of Radiation Sciences.
(English)Manuscript (preprint) (Other academic)
National Category
Neurosciences
Identifiers
URN: urn:nbn:se:umu:diva-82512OAI: oai:DiVA.org:umu-82512DiVA: diva2:661665
Available from: 2013-11-04 Created: 2013-11-04 Last updated: 2016-03-07Bibliographically approved
In thesis
1. Attrition in Studies of Cognitive Aging
Open this publication in new window or tab >>Attrition in Studies of Cognitive Aging
2013 (English)Doctoral thesis, comprehensive summary (Other academic)
Alternative title[sv]
Bortfall i studier av kognitivt åldrande
Abstract [en]

Longitudinal studies of cognition are preferred to cross-sectional stud- ies, since they offer a direct assessment of age-related cognitive change (within-person change). Statistical methods for analyzing age-related change are widely available. There are, however, a number of challenges accompanying such analyzes, including cohort differences, ceiling- and floor effects, and attrition. These difficulties challenge the analyst and puts stringent requirements on the statistical method being used.

The objective of Paper I is to develop a classifying method to study discrepancies in age-related cognitive change. The method needs to take into account the complex issues accompanying studies of cognitive aging, and specifically work out issues related to attrition. In a second step, we aim to identify predictors explaining stability or decline in cognitive performance in relation to demographic, life-style, health-related, and genetic factors.

In the second paper, which is a continuation of Paper I, we investigate brain characteristics, structural and functional, that differ between suc- cessful aging elderly and elderly with an average cognitive performance over 15-20 years.

In Paper III we develop a Bayesian model to estimate the causal effect of living arrangement (living alone versus living with someone) on cog- nitive decline. The model must balance confounding variables between the two living arrangement groups as well as account for non-ignorable attrition. This is achieved by combining propensity score matching with a pattern mixture model for longitudinal data.

In paper IV, the objective is to adapt and implement available impu- tation methods to longitudinal fMRI data, where some subjects are lost to follow-up. We apply these missing data methods to a real dataset, and evaluate these methods in a simulation study.

Place, publisher, year, edition, pages
Umeå: Umeå universitet, 2013. 21 p.
Series
Statistical studies, ISSN 1100-8989 ; 47
Keyword
Attrition, missing data, age-related cognitive change, non- ignorable dropout, monotone missing pattern, mixture models, pattern- mixture models, imputation
National Category
Other Social Sciences not elsewhere specified
Research subject
Statistics
Identifiers
urn:nbn:se:umu:diva-82514 (URN)978-91-7459-760-8 (ISBN)
Public defence
2013-11-29, Humanisthuset, Hörsal F, Umeå universitet, Umeå, 10:15 (English)
Opponent
Supervisors
Available from: 2013-11-08 Created: 2013-11-04 Last updated: 2016-03-07Bibliographically approved

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Josefsson, MariaLundquist, AndersNyberg, Lars

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StatisticsUmeå Centre for Functional Brain Imaging (UFBI)Department of Integrative Medical Biology (IMB)Department of Radiation Sciences
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CiteExportLink to record
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