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Regression Models for Log-Normal Data: Comparing Different Methods for Quantifying the Association between Abdominal Adiposity and Biomarkers of Inflammation

Journal article
Authors Sara Gustavsson
Björn Fagerberg
Gerd Sällsten
Eva M. Andersson
Published in International Journal of Environmental Research and Public Health
Volume 11
Issue 4
Pages 3521-3539
ISSN 1660-4601
Publication year 2014
Published at Wallenberg Laboratory
Institute of Medicine, Department of Public Health and Community Medicine, Section of Occupational and environmental medicine
Institute of Medicine, Department of Molecular and Clinical Medicine
Pages 3521-3539
Language en
Links www.mdpi.com/1660-4601/11/4/3521/
Keywords linear regression model, log-normal distribution, heteroscedasticity, biomarkers of inflammation, insulin resistance, simulation study
Subject categories Epidemiology

Abstract

We compared six methods for regression on log-normal heteroscedastic data with respect to the estimated associations with explanatory factors (bias and standard error) and the estimated expected outcome (bias and confidence interval). Method comparisons were based on results from a simulation study, and also the estimation of the association between abdominal adiposity and two biomarkers; C-Reactive Protein (CRP) (inflammation marker,) and Insulin Resistance (HOMA-IR) (marker of insulin resistance). Five of the methods provide unbiased estimates of the associations and the expected outcome; two of them provide confidence intervals with correct coverage.

Page Manager: Webmaster|Last update: 9/11/2012
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