Activity Number:
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508
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Type:
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Contributed
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Date/Time:
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Wednesday, August 3, 2016 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Nonparametric Statistics
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Abstract #319909
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Title:
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Multiple Imputation Method Based on Weighted Quantile Regression Models for Longitudinal Censored Biomarker Data with Missing Early Visits
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Author(s):
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MinJae Lee* and Mohammad H. Rahbar and John D. Reveille and Michael Weisman and Michael M. Ward and Lianne Gensler and Matthew Brown
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Companies:
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The University of Texas Health Science Center at Houston and The University of Texas Health Science Center at Houston and The University of Texas Health Science Center at Houston and Cedars-Sinai Medical Center and National Institute of Arthritis and Musculoskeletal and Skin Diseases and University of California at San Francisco and University of Queensland Diamantina Institute
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Keywords:
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Left Censored Data ;
Detection Limit ;
Biomarker ;
Multiple Imputation ;
Quantile Regression ;
Genetics and Ankylosing Spondylitis (AS) Pathogenesis study
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Abstract:
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In some biomedical cohort studies, the biomarker data can be censored subject to the detection limits of the assay and it is also possible that the data are not collected in certain time points during follow-up in the cohort. Inappropriate handling of these two issues could lead to biased estimation of regression parameters. We propose the Multiple Imputation (MI) that is based on censored quantile regression (CQR) that not only accounts for censoring, but also applies the inverse probability weighting technique to adjust for the data with missing values in early visits. Through a simulation study we evaluate the performance and robustness of our method under different scenarios. Our findings indicate that the proposed approach performs better than other MI methods and complete case analyses given moderate levels of censoring. We demonstrate application of our method to data from Genetics and Ankylosing Spondylitis (AS) Pathogenesis study with an aim to examine the longitudinal association between C-reactive protein (CRP) level and radiographic severity in AS when CRP levels were not collected in the first part of study period and also censored due to the detection limit.
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Authors who are presenting talks have a * after their name.