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A statistical model for interpreting computerized dynamic posturography dataComputerized dynamic posturography (CDP) is widely used for assessment of altered balance control. CDP trials are quantified using the equilibrium score (ES), which ranges from zero to 100, as a decreasing function of peak sway angle. The problem of how best to model and analyze ESs from a controlled study is considered. The ES often exhibits a skewed distribution in repeated trials, which can lead to incorrect inference when applying standard regression or analysis of variance models. Furthermore, CDP trials are terminated when a patient loses balance. In these situations, the ES is not observable, but is assigned the lowest possible score--zero. As a result, the response variable has a mixed discrete-continuous distribution, further compromising inference obtained by standard statistical methods. Here, we develop alternative methodology for analyzing ESs under a stochastic model extending the ES to a continuous latent random variable that always exists, but is unobserved in the event of a fall. Loss of balance occurs conditionally, with probability depending on the realized latent ES. After fitting the model by a form of quasi-maximum-likelihood, one may perform statistical inference to assess the effects of explanatory variables. An example is provided, using data from the NIH/NIA Baltimore Longitudinal Study on Aging.
Document ID
20040088387
Document Type
Reprint (Version printed in journal)
External Source(s)
Authors
Feiveson, Alan H. (NASA Johnson Space Center Houston TX United States)
Metter, E. Jeffrey
Paloski, William H.
Date Acquired
August 21, 2013
Publication Date
April 1, 2002
Publication Information
Publication: IEEE transactions on bio-medical engineering
Volume: 49
Issue: 4
ISSN: 0018-9294
Subject Category
Life Sciences (General)
Funding Number(s)
CONTRACT_GRANT: 1Z01AG00014-41
CONTRACT_GRANT: 205
Distribution Limits
Public
Copyright
Other
Keywords
NASA Discipline Neuroscience
NASA Center JSC