2 citations · 3 across the 4 of their papers we have counts for
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Bayesian semiparametric modelling of biomarker variability in joint models
Sida Chen, Jessica K. Barrett, Marco Palma +2
There is growing interest in the role of within-individual variability (WIV) in biomarker trajectories for assessing disease risk and progression. A trajectory-based definition tha…
Assessing the impact of variance heterogeneity and misspecification in mixed-effects location-scale models
Vincent Jeanselme, Marco Palma, Jessica K Barrett
Linear Mixed Model (LMM) is a common statistical approach to model the relation between exposure and outcome while capturing individual variability through random effects. However,…
A Bayesian location-scale joint model for time-to-event and multivariate longitudinal data with association based on within-individual variability
Marco Palma, Ruth H Keogh, Siobhán B Carr +5
Within-individual variability of health indicators measured over time is becoming commonly used to inform about disease progression. Simple summary statistics (e.g. the standard de…
Bayesian shared parameter joint models for heterogeneous populations
Sida Chen, Danilo Alvares, Marco Palma +1
Joint models (JMs) for longitudinal and time-to-event data are an important class of biostatistical models in health and medical research. When the study population consists of het…