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양적 형질의 유전적 관련성 연구에서 치료 효과를 보정하기 위한 통계학적 방법의 비교

Other Titles
 A comparison of statistical methods for adjusting the treatment effects in genetic association studies of quantitative traits 
Authors
 한경화  ;  임길섭  ;  박성하  ;  장양수  ;  송기준 
Citation
 Journal of Korea Society of Endocrinology (대한내분비학회지), Vol.34(1) : 53-62, 2009 
Journal Title
 Journal of Korea Society of Endocrinology (대한내분비학회지) 
Issue Date
2009
Keywords
quantitative trait ; genetic association ; treatment effect adjustment ; regression ; censored regression
Abstract
Objective: This paper aims to compare the performance of regression-based statistical approaches that were currently used or advocated to adjust a treatment effect. Methods: The six methods used to compare their relative performance were: excluding treated individuals from data, no adjustment for treatment effect, modelling treatment as a covariate(indicator variable), non-parametric adjustment of treatment, adding a constant value to measurements for treated individuals, and censored normal regression. We applied these methods to real genetic and clinical data from Yonsei cardiovascular genome center to demonstrate a pattern of their behaviour. Results: Two of the adjustment methods were more powerful than other methods for analysis of genetic association with serum lipid profiles. These were: no adjustment to the observed lipid profiles in treated subjects, non-parametric adjustment method based on averaging ordered residuals. Conclusion: Non-parametric adjustment method based on averaging ordered residuals and no adjustment to the observed lipid profiles in treated subjects can effectively adjust the distorting effect of lipid-lowering drug and recover a marked loss in statistical power. Also, in genetic association studies of continuous traits that distortion arising from a treatment effect really matters, we proposed to use the appropriate methods that are more effective and straightforward to implement
Files in This Item:
T200903077.pdf Download
Appears in Collections:
1. College of Medicine (의과대학) > Yonsei Biomedical Research Center (연세의생명연구원) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Biomedical Systems Informatics (의생명시스템정보학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Internal Medicine (내과학교실) > 1. Journal Papers
Yonsei Authors
Park, Sung Ha(박성하) ORCID logo https://orcid.org/0000-0001-5362-478X
Song, Ki Jun(송기준) ORCID logo https://orcid.org/0000-0003-2505-4112
Jang, Yang Soo(장양수) ORCID logo https://orcid.org/0000-0002-2169-3112
Han, Kyung Hwa(한경화)
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/104643
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