Modeling of correlated cognitive function and functional disability outcomes with bounded and missing data in a longitudinal aging study.

Journal: Behavior research methods

Volume: 54

Issue: 6

Year of Publication: 2022

Affiliated Institutions:  StatsDecide Analytics and Consulting Ltd, P.O. Box -, Nakuru, Kenya. agogogeorge@gmail.com. School of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, Pietermaritzburg Campus, Pietermaritzburg, South Africa. National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, , China. Department of Big Data in Health Science and Center for Clinical Big Data and Analytics, School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.

Abstract summary 

Longitudinal studies of correlated cognitive and disability outcomes among older adults are characterized by missing data due to death or loss to follow-up from deteriorating health conditions. The Mini-Mental State Examination (MMSE) score for assessing cognitive function ranges from a minimum of 0 (floor) to a maximum of 30 (ceiling). To study the risk factors of cognitive function and functional disability, we propose a shared parameter model to handle missingness, correlation between outcomes, and the floor and ceiling effects of the MMSE measurements. The shared random effects in the proposed model handle missingness (either missing at random or missing not at random) and correlation between these outcomes, while the Tobit distribution handles the floor and ceiling effects of the MMSE measurements. We used data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) and a simulation study. By ignoring the MMSE floor and ceiling effects in the analyses of the CLHLS, the association of systolic blood pressure with cognitive function was not significant and the association of age with cognitive function was lower by 16.6% (from -6.237 to -5.201). By ignoring the MMSE floor and ceiling effects in the simulation study, the relative bias in the estimated association of female gender with cognitive function was 43 times higher (from -0.01 to -0.44). The estimated associations obtained with data missing at random were smaller than those with data missing not at random, demonstrating how the missing data mechanism affects the analytic results. Our work underscores the importance of proper model specification in longitudinal analysis of correlated outcomes subject to missingness and bounded values.

Authors & Co-authors:  Agogo Mwambi Shi Liu

Study Outcome 

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Statistics
Citations :  Agogo, G. O., Ramsey, C. M., Gnjidic, D., Moga, D. C., & Allore, H. (2018). Longitudinal associations between different dementia diagnoses and medication use jointly accounting for dropout. Int Psychogeriatr, 30(10), 1477-1487.
Authors :  4
Identifiers
Doi : 10.3758/s13428-022-01796-6
SSN : 1554-3528
Study Population
Female
Mesh Terms
Humans
Other Terms
Correlated outcomes;Joint modeling;Mini-Mental State Examination;Missing data;Shared parameter model;Tobit regression
Study Design
Study Approach
Country of Study
Kenya
Publication Country
United States