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J Health Info Stat 2009;34(1):53-63.
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| 양적 형질의 유전적 관련성 연구에서 치료 효과를 보정하기 위한 통계학적 방법의 비교 |
| 한경화 , 임길섭 , 박성하 , 장양수 , 송기준 |
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| A comparison of statistical methods for adjusting the treatment effects in genetic association studies of quantitative traits |
| Kyung Hwa Han , Kil Seob Lim , Sung Ha Park , Yang Soo Jang , Ki Jun Song |
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| 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. |
| Key words:
quantitative trait, genetic association, treatment effect adjustment, regression, censored regression |
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