Work

Bayesian partial linear model for skewed longitudinal data

Year: 2015

Type: article

Abstract: Unlike majority of current statistical models and methods focusing on mean response for highly skewed longitudinal data, we present a novel model for such data accommodating a partially linear median regression function, a skewed error distribution and within subject association structures. We provide theoretical justifications for our methods including asymptotic properties of the posterior and associated semiparametric Bayesian estimators. We also provide simulation studies to investigate the finite sample properties of our methods. Several advantages of our method compared with existing methods are demonstrated via analysis of a cardiotoxicity study of children of HIV-infected mothers.

Source: Biostatistics

DOI: 10.1093/biostatistics/kxv005

Authors: Yuanyuan Tang, Debajyoti Sinha, Debdeep Pati, Stuart Lipsitz, Steven Lipshultz

Institutions: Florida State University, Brigham and Women's Hospital, Wayne State University, Children's Hospital of Michigan

Language: English

Topic: Statistical Methods and Bayesian Inference

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: green

Funders: National Institutes of Health, National Cancer Institute