Predictive Partly Conditional Models for Longitudinal Ordinal Outcomes with Application to Alzheimer’s Disease Progression

Jacquelyn E. Neal (), Panpan Zhang () and Dandan Liu ()
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Jacquelyn E. Neal: Vanderbilt University
Panpan Zhang: Vanderbilt University
Dandan Liu: Vanderbilt University

Statistics in Biosciences, 2025, vol. 17, issue 2, No 1, 233-250

Abstract: Abstract Assessing time-dependent risk factors in relation to the risk of disease progression is challenging, yet important, especially for chronic diseases with slow progression. In this paper, the partly conditional model is extended for characterizing disease progression at time t with longitudinal ordinal outcomes in the presence of time-dependent covariates at time s $$(s

Keywords: Partly conditional model; Disease progression; Longitudinal ordinal outcome; Time-dependent risk factors; Alzheimer’s disease (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s12561-024-09433-w

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