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Evaluation of regression methods for log-normal data - linear models for environmental exposure and biomarker outcomes

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Title: Evaluation of regression methods for log-normal data - linear models for environmental exposure and biomarker outcomes
Authors: Gustavsson, Sara
Issue Date: 3-Mar-2015
University: University of Gothenburg. Sahlgrenska Academy
Institution: Institute of Medicine. Department of Public Health and Community Medicine
Parts of work: I. Gustavsson, S. M., Johannesson, S., Sallsten, G., and Andersson, E. M. (2012). Linear Maximum Likelihood Regression Analysis for Untransformed Log-Normally Distributed Data. Open Journal of Statistics 2, 389-400.

II. Gustavsson, S., Fagerberg, B., Sallsten, G., and Andersson, E. (2014). Regression Models for Log-Normal Data: Comparing Different Methods for Quantifying the Association between Abdominal Adiposity and Biomarkers of Inflammation and Insulin Resistance. International Journal of Environmental Research and Public Health 11, 3521-3539.

III. Gustavsson S., and Andersson E. M., Small-Sample Inference for Linear Regression on Untransformed Log-Normal Data. Submitted for publication.

IV. Gustavsson S., Akerstrom M., Sallsten G., and Andersson E. M., Linear Regression on Log-Normal Data with Repeated Measurements. Submitted for publication.
Date of Defence: 2015-03-19
Disputation: Torsdag den 19 mars, kl. 9:00, Hörsal Hamberger, Medicinaregatan 16
Degree: Doctor of Philosophy (Medicine)
Publication type: Doctoral thesis
Keywords: log-normal distribution
linear models
absolute effects
Abstract: The identification and quantification of associations between variables is often of interest in occupational and environmental research, and regression analysis is commonly used to assess these associations. While exposures and biological data often have a positive skewness and can be approximated with the log-normal distribution, much of the inference in regression analysis is based on the normal distribution. A common approach is therefore to log-transform the data before the regression analys... more
ISBN: 978-91-628-9295-1
Appears in Collections:Doctoral Theses from Sahlgrenska Academy
Doctoral Theses from University of Gothenburg / Doktorsavhandlingar från Göteborgs universitet
Doctoral Theses / Doktorsavhandlingar Institutionen för medicin



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