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

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,...

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Detalles Bibliográficos
Autores principales: Gustavsson, Sara, Fagerberg, Björn, Sallsten, Gerd, Andersson, Eva M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2014
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4024993/
https://www.ncbi.nlm.nih.gov/pubmed/24681553
http://dx.doi.org/10.3390/ijerph110403521
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author Gustavsson, Sara
Fagerberg, Björn
Sallsten, Gerd
Andersson, Eva M.
author_facet Gustavsson, Sara
Fagerberg, Björn
Sallsten, Gerd
Andersson, Eva M.
author_sort Gustavsson, Sara
collection PubMed
description 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.
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spelling pubmed-40249932014-05-19 Regression Models for Log-Normal Data: Comparing Different Methods for Quantifying the Association between Abdominal Adiposity and Biomarkers of Inflammation and Insulin Resistance Gustavsson, Sara Fagerberg, Björn Sallsten, Gerd Andersson, Eva M. Int J Environ Res Public Health Article 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. MDPI 2014-03-27 2014-04 /pmc/articles/PMC4024993/ /pubmed/24681553 http://dx.doi.org/10.3390/ijerph110403521 Text en © 2014 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Article
Gustavsson, Sara
Fagerberg, Björn
Sallsten, Gerd
Andersson, Eva M.
Regression Models for Log-Normal Data: Comparing Different Methods for Quantifying the Association between Abdominal Adiposity and Biomarkers of Inflammation and Insulin Resistance
title Regression Models for Log-Normal Data: Comparing Different Methods for Quantifying the Association between Abdominal Adiposity and Biomarkers of Inflammation and Insulin Resistance
title_full Regression Models for Log-Normal Data: Comparing Different Methods for Quantifying the Association between Abdominal Adiposity and Biomarkers of Inflammation and Insulin Resistance
title_fullStr Regression Models for Log-Normal Data: Comparing Different Methods for Quantifying the Association between Abdominal Adiposity and Biomarkers of Inflammation and Insulin Resistance
title_full_unstemmed Regression Models for Log-Normal Data: Comparing Different Methods for Quantifying the Association between Abdominal Adiposity and Biomarkers of Inflammation and Insulin Resistance
title_short Regression Models for Log-Normal Data: Comparing Different Methods for Quantifying the Association between Abdominal Adiposity and Biomarkers of Inflammation and Insulin Resistance
title_sort regression models for log-normal data: comparing different methods for quantifying the association between abdominal adiposity and biomarkers of inflammation and insulin resistance
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4024993/
https://www.ncbi.nlm.nih.gov/pubmed/24681553
http://dx.doi.org/10.3390/ijerph110403521
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