Statistical analysis of time-to-event data with noncompliance in randomized clinical trials
Principal Investigator
Name
Shuwei Li
Degrees
Ph.D
Institution
Emory University
Position Title
Postdoc
Email
About this CDAS Project
Study
PLCO
(Learn more about this study)
Project ID
PLCO-518
Initial CDAS Request Approval
Aug 29, 2019
Title
Statistical analysis of time-to-event data with noncompliance in randomized clinical trials
Summary
We would like to apply and use the Colorectal and Prostate data from the PLCO study, which, we promise, are only used for scientific research.
Our reseach interests are mainly focused on survival analysis, logitudianl data analysis and high dimensional data analysis.
Therefore, by the PLCO data, we would like to develop novel statistical methods for the analysis of interval-censored data, noncompliance in randomized study and variable selection problem.
I think our work may provide a new insight for the analysis of interval censored data with data that are always ignored in practice, and also may help find some useful factors in reducing the risk of PLCO cancer occurrence or may be benifit for the early detection of the cancer.
Our reseach interests are mainly focused on survival analysis, logitudianl data analysis and high dimensional data analysis.
Therefore, by the PLCO data, we would like to develop novel statistical methods for the analysis of interval-censored data, noncompliance in randomized study and variable selection problem.
I think our work may provide a new insight for the analysis of interval censored data with data that are always ignored in practice, and also may help find some useful factors in reducing the risk of PLCO cancer occurrence or may be benifit for the early detection of the cancer.
Aims
Develop novel statistical methods for the interval-censored data with noncompliance.
Develop variable selection methods for the survival data with complex features.
Develop R packages that may help the researchers use our proposed methods.
Collaborators
Limin Peng Emory University
Related Publications
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Causal Proportional Hazards Estimation with a Binary Instrumental Variable.
Kianian B, Kim JI, Fine JP, Peng L
Stat Sin. 2021 Apr; Volume 31 (Issue 2): Pages 673-699 PUBMED