Analysis of Dependently Truncated Data in Cox Framework

Details

• Alternative Title:
  Commun Stat Simul Comput
• Personal Author:
  Liu, Yang ; Li, Ji ; Zhang, Xu
• Description:
  Truncation is a known feature of bone marrow transplant (BMT) registry data, for which the survival time of a leukemia patient is left truncated by the waiting time to transplant. It was recently noted that a longer waiting time was linked to poorer survival. A straightforward solution is a Cox model on the survival time with the waiting time as both truncation variable and covariate. The Cox model should also include other recognized risk factors as covariates. In this paper we focus on estimating the distribution function of waiting time and the probability of selection under the aforementioned Cox model.
• Keywords:
  Cox Model Dependent Truncation Inverse Probability Weighting
• Source:
  Commun Stat Simul Comput. 47(6):1677-1695
• Pubmed ID:
  28725104
• Pubmed Central ID:
  PMC5513481
• Document Type:
  Journal Article
• Funding:
  CC999999/Intramural CDC HHSUnited States/ ; UL1 TR000371/TR/NCATS NIH HHSUnited States/
• Volume:
  47
• Issue:
  6
• Collection(s):
  CDC Public Access
• Main Document Checksum:
  urn:sha256:e7f010866dc231f13f2850e5eba70ff6a39bf314fb3cf0caa1528fa9dc6d9a3b
• Download URL:
  https://stacks.cdc.gov/view/cdc/47522/cdc_47522_DS1.pdf
• File Type:
  [PDF - 597.81 KB ]