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Perform Cox PH, time-dependent Cox, and Joint Model for longitudinal and survival data to study cirrhosis

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Cirrhosis-study

  • Study the association between serum bilirubin and overall survival of cirrhosis patients using Cox Proportional Hazards model, time-dependent Cox model and Joint model for longitudinal and survival data
  • Compare results from three models

References:

  • Rizopoulos, Dimitris. Joint models for longitudinal and time-to-event data: With applications in R. CRC press, 2012.
  • Rizopoulos, Dimitris. "JM: An R package for the joint modelling of longitudinal and time-to-event data." Journal of Statistical Software (Online) 35.9 (2010): 1-33.
  • Schober, Patrick, and Thomas R. Vetter. "Survival analysis and interpretation of time-to-event data: the tortoise and the hare." Anesthesia and analgesia 127.3 (2018): 792.
  • Albert, Paul S. "Longitudinal data analysis (repeated measures) in clinical trials." Statistics in medicine 18.13 (1999): 1707-1732.
  • Harrell Jr, Frank E., Kerry L. Lee, and Daniel B. Mark. "Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors." Statistics in medicine 15.4 (1996): 361-387.

@AmeliaTran Summer 2020

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Perform Cox PH, time-dependent Cox, and Joint Model for longitudinal and survival data to study cirrhosis

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