Joint latent class models for longitudinal and time-to-event data: A review:
Cécile Proust-Lima,Mbéry Sène,Mbéry Sène,Jeremy M. G. Taylor,Hélène Jacqmin-Gadda,Hélène Jacqmin-Gadda +5 more
TLDR
This article aims at giving an overview of joint latent class modelling, especially in the prediction context, by introducing the model, discussing estimation and goodness-of-fit, and comparing it with the shared random-effect model.Abstract:
Most statistical developments in the joint modelling area have focused on the shared random-effect models that include characteristics of the longitudinal marker as predictors in the model for the time-to-event. A less well-known approach is the joint latent class model which consists in assuming that a latent class structure entirely captures the correlation between the longitudinal marker trajectory and the risk of the event. Owing to its flexibility in modelling the dependency between the longitudinal marker and the event time, as well as its ability to include covariates, the joint latent class model may be particularly suited for prediction problems. This article aims at giving an overview of joint latent class modelling, especially in the prediction context. The authors introduce the model, discuss estimation and goodness-of-fit, and compare it with the shared random-effect model. Then, dynamic predictive tools derived from joint latent class models, as well as measures to evaluate their dynamic pre...read more
Citations
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Estimation of extended mixed models using latent classes and latent processes: the R package lcmm
TL;DR: The R package lcmm as mentioned in this paper provides a series of functions to estimate statistical models based on linear mixed model theory, including the estimation of mixed models and latent class mixed models for Gaussian longitudinal outcomes.
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Rethinking the dose-response relationship between usage and outcome in an online intervention for depression: randomized controlled trial.
Liesje Donkin,Ian B. Hickie,Helen Christensen,Sharon L. Naismith,Bruce Neal,Nicole Cockayne,Nick Glozier +6 more
TL;DR: Only one objective measure of usage was independently associated with better outcome of a Web-based intervention of known effectiveness, and medium level users appeared to have little additional benefit compared to low users indicating that assumptions of a linear relationship between use and outcome may be too simplistic.
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Joint modelling of repeated measurement and time-to-event data: an introductory tutorial
TL;DR: Joint models should be preferred for simultaneous analyses of repeated measurement and survival data, especially when the former is measured with error and the association between the underlying error-free measurement process and the hazard for survival is of scientific interest.
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Joint modelling of time-to-event and multivariate longitudinal outcomes: recent developments and issues
TL;DR: Although, in an era of personalized medicine, the value of multivariate joint modelling has been established, researchers are currently limited in their ability to fit these models routinely.
Journal ArticleDOI
Real-Time Individual Predictions of Prostate Cancer Recurrence Using Joint Models
Jeremy M. G. Taylor,Yongseok Park,Donna P. Ankerst,Donna P. Ankerst,Cécile Proust-Lima,Scott Williams,Larry L. Kestin,K. Bae,Tom Pickles,Howard M. Sandler +9 more
TL;DR: The methodology for giving the probability of recurrence for a new patient, as implemented on a web‐based calculator uses a joint longitudinal survival model that uses the longitudinal PSA measures from a new patients.
References
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