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Activity Number: 344 - Semiparametric Modeling
Type: Contributed
Date/Time: Tuesday, July 31, 2018 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract #329985 Presentation
Title: An Application of Covariate-Adjusted Partial Spearman's Rank Correlations with Probability-Scale Residuals
Author(s): Cathy A Jenkins* and John R Koethe and Timothy R Sterling and Spyros A Kalams and Bryan E Shepherd
Companies: Vanderbilt University Medical Center and Vanderbilt University School of Medicine and Vanderbilt University School of Medicine and Vanderbilt University School of Medicine and Vanderbilt University School of Medicine
Keywords: Probability-scale residuals; Spearman's rank correlation; HIV

When engaging in hypothesis generating research, it is important to summarize the relationships of interest in a meaningful way. Correlation coefficients are a common summary statistic that describe the strength and direction of relationships. Simple summary methods use unadjusted correlation coefficients such as Pearson or Spearman's; however, failing to adjust for covariates may result in misleading conclusions. Partial correlations allow for adjustment variables, but traditional approaches for measuring partial rank correlations lack a theoretical foundation. Liu et al (Biometrics, in press) proposed an alternative estimator for covariate-adjusted partial Spearman's rank correlations using probability-scale residuals (PSRs). We apply this method to explore the relationships between body composition and markers of innate and adaptive immune status in HIV+ subjects. Three measures of adiposity were considered - body mass index, fat mass index, and plasma leptin. Immunologic markers included soluble cytokines and other biomarkers, CD4+ and CD8+ T cell subsets.

Authors who are presenting talks have a * after their name.

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