1.7k citations · 1.8k across the 12 of their papers we have counts for
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Using Joint Models for Longitudinal and Time-to-Event Data to Investigate the Causal Effect of Salvage Therapy after Prostatectomy
Dimitris Rizopoulos, Jeremy M. G. Taylor, Grigorios Papageorgiou +1
Prostate cancer patients who undergo prostatectomy are closely monitored for recurrence and metastasis using routine prostate-specific antigen (PSA) measurements. When PSA levels r…
Optimizing Dynamic Predictions from Joint Models using Super Learning
Dimitris Rizopoulos, Jeremy M. G. Taylor
Joint models for longitudinal and time-to-event data are often employed to calculate dynamic individualized predictions used in numerous applications of precision medicine. Two com…
A Continuous-Time Dynamic Factor Model for Intensive Longitudinal Data Arising from Mobile Health Studies
Madeline R. Abbott, Walter H. Dempsey, Inbal Nahum-Shani +3
Intensive longitudinal data (ILD) collected in mobile health (mHealth) studies contain rich information on multiple outcomes measured frequently over time that have the potential t…