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

Sara Gustavsson, Björn Fagerberg, Gerd Sallsten and Eva M. Andersson
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Sara Gustavsson: Occupational and Environmental Medicine, Sahlgrenska University Hospital and Academy, University Of Gothenburg, Gothenburg SE-405 30, Sweden
Björn Fagerberg: Wallenberg Laboratory, Sahlgrenska Center for Cardiovascular and Metabolic Research, Sahlgrenska University Hospital, Gothenburg SE-413 45, Sweden
Gerd Sallsten: Occupational and Environmental Medicine, Sahlgrenska University Hospital and Academy, University Of Gothenburg, Gothenburg SE-405 30, Sweden
Eva M. Andersson: Occupational and Environmental Medicine, Sahlgrenska University Hospital and Academy, University Of Gothenburg, Gothenburg SE-405 30, Sweden

IJERPH, 2014, vol. 11, issue 4, 1-19

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.

Keywords: linear regression model; log-normal distribution; heteroscedasticity; biomarkers of inflammation; insulin resistance; simulation study (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2014
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