Fully exponential Laplace approximations for the joint modelling of survival and longitudinal data

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Dynamic Predictions and Prospective Accuracy in Joint Models for Longitudinal and Time‐to‐Event Data (2011, methodology): “Furthermore, Rizopoulos et al. (2009) and Ye, Lin, and Taylor (2008) have recently discussed the use of Laplace approximations for joint models, which can be especially useful in high-dimensional randomeffects settings (e.g., when splines or high-order polynomials are used in the random-effects…”
JM: An R package for the joint modelling of longitudinal and time-to-event data (2010, methodology): “We expect the multivariate t proposals to work satisfactorily in this setting because, as it has been recently shown by Rizopoulos et al. (2008), as ni (the number of longitudinal measurements for subject i) increases, the leading term of the log posterior distribution of the random effects is the l”
Random Effects Models for Longitudinal Data (2010, methodology): “Furthermore, Rizopoulos, Verbeke, and Lesaffre (2009b) have recently discussed the use of Laplace approximations for joint models, that can be especially useful in high-dimensional 26 random-effects settings (e.g., when splines are used in random-effects design matrix).”