Key result
A novel stochastic model extending the equilibrium score to a continuous latent random variable was developed to address the skewed and mixed discrete-continuous distribution of posturography data.
The proposed statistical model addresses the skewed and mixed discrete-continuous distribution of equilibrium scores in computerized dynamic posturography, improving inference compared to standard methods.
May refine posturography analysis; leaves open prospective validation before clinical adoption.
Computerized 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.
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Feiveson et al. (2002) studied Altered balance control. Stochastic model extending the equilibrium score to a continuous latent random variable vs. Standard regression or analysis of variance models was evaluated. A novel stochastic model extending the equilibrium score to a continuous latent random variable was developed to address the skewed and mixed discrete-continuous distribution of posturography data.
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