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Linear regression with a randomly censored covariate: Application to an Alzheimer’s study
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Journal of Applied & Computational Mathematics

ISSN: 2168-9679

Open Access

Linear regression with a randomly censored covariate: Application to an Alzheimer’s study


4th International Conference and Exhibition on Biometrics & Biostatistics

November 16-18, 2015 San Antonio, USA

Folefac D Atem

University of Texas, USA

Posters-Accepted Abstracts: J Appl Computat Math

Abstract :

The association between maternal age of onset of dementia and beta-amyloid deposition (measured by in vivo PET imaging) of offspring is of interest to assess in a study of cognitively normal individuals over the age of 60. In a regression model for beta-amyloid, special methods are required due to the random right censoring of the covariate of maternal age of onset of dementia. The prior literature has proposed methods to address the problem of censoring due to assay limit of detection, but not random censoring. We propose imputation methods and a survival regression method that do not require parametric assumptions on the distribution of the censored covariate. In simulation studies, we compare these methods to the simple, but inefficient complete case analysis, and to threshold approaches. We apply the methods to the Alzheimerâ??s study.

Biography :

Email: Folefac.D.Atem@uth.tmc.edu

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Citations: 1282

Journal of Applied & Computational Mathematics received 1282 citations as per Google Scholar report

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