Joint Models for Longitudinal and Time-to-Event Data

Book description

Longitudinal studies often investigate how a marker that is repeatedly measured in time is associated with a time to an event of interest. An example is prostate cancer studies where longitudinal PSA level measurements are collected in conjunction with the time-to-recurrence. This book provides a full treatment of joint models for longitudinal and time-to-event data. The content is explanatory rather than mathematically rigorous and emphasizes applications. All illustrations put forward are available in the R programming language via the freely available package JM written by the author.

Table of contents

  1. Front Cover (1/2)
  2. Front Cover (2/2)
  3. Dedication (1/2)
  4. Dedication (2/2)
  5. Contents
  6. Preface (1/2)
  7. Preface (2/2)
  8. 1. Introduction (1/3)
  9. 1. Introduction (2/3)
  10. 1. Introduction (3/3)
  11. 2. Longitudinal Data Analysis (1/4)
  12. 2. Longitudinal Data Analysis (2/4)
  13. 2. Longitudinal Data Analysis (3/4)
  14. 2. Longitudinal Data Analysis (4/4)
  15. 3. Analysis of Event Time Data (1/4)
  16. 3. Analysis of Event Time Data (2/4)
  17. 3. Analysis of Event Time Data (3/4)
  18. 3. Analysis of Event Time Data (4/4)
  19. 4. Joint Models for Longitudinal and Time-to-Event Data (1/10)
  20. 4. Joint Models for Longitudinal and Time-to-Event Data (2/10)
  21. 4. Joint Models for Longitudinal and Time-to-Event Data (3/10)
  22. 4. Joint Models for Longitudinal and Time-to-Event Data (4/10)
  23. 4. Joint Models for Longitudinal and Time-to-Event Data (5/10)
  24. 4. Joint Models for Longitudinal and Time-to-Event Data (6/10)
  25. 4. Joint Models for Longitudinal and Time-to-Event Data (7/10)
  26. 4. Joint Models for Longitudinal and Time-to-Event Data (8/10)
  27. 4. Joint Models for Longitudinal and Time-to-Event Data (9/10)
  28. 4. Joint Models for Longitudinal and Time-to-Event Data (10/10)
  29. 5. Extensions of the Standard Joint Model (1/10)
  30. 5. Extensions of the Standard Joint Model (2/10)
  31. 5. Extensions of the Standard Joint Model (3/10)
  32. 5. Extensions of the Standard Joint Model (4/10)
  33. 5. Extensions of the Standard Joint Model (5/10)
  34. 5. Extensions of the Standard Joint Model (6/10)
  35. 5. Extensions of the Standard Joint Model (7/10)
  36. 5. Extensions of the Standard Joint Model (8/10)
  37. 5. Extensions of the Standard Joint Model (9/10)
  38. 5. Extensions of the Standard Joint Model (10/10)
  39. 6. Joint Model Diagnostics (1/6)
  40. 6. Joint Model Diagnostics (2/6)
  41. 6. Joint Model Diagnostics (3/6)
  42. 6. Joint Model Diagnostics (4/6)
  43. 6. Joint Model Diagnostics (5/6)
  44. 6. Joint Model Diagnostics (6/6)
  45. 7. Prediction and Accuracy in Joint Models (1/10)
  46. 7. Prediction and Accuracy in Joint Models (2/10)
  47. 7. Prediction and Accuracy in Joint Models (3/10)
  48. 7. Prediction and Accuracy in Joint Models (4/10)
  49. 7. Prediction and Accuracy in Joint Models (5/10)
  50. 7. Prediction and Accuracy in Joint Models (6/10)
  51. 7. Prediction and Accuracy in Joint Models (7/10)
  52. 7. Prediction and Accuracy in Joint Models (8/10)
  53. 7. Prediction and Accuracy in Joint Models (9/10)
  54. 7. Prediction and Accuracy in Joint Models (10/10)
  55. A. A Brief Introduction to R (1/2)
  56. A. A Brief Introduction to R (2/2)
  57. B. The EM Algorithm for Joint Models (1/2)
  58. B. The EM Algorithm for Joint Models (2/2)
  59. C. Structure of the JM Package
  60. References (1/4)
  61. References (2/4)
  62. References (3/4)
  63. References (4/4)

Product information

  • Title: Joint Models for Longitudinal and Time-to-Event Data
  • Author(s): Dimitris Rizopoulos
  • Release date: June 2012
  • Publisher(s): CRC Press
  • ISBN: 9781439872871