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Comment
. 2012 Dec;36(8):890-4.
doi: 10.1002/gepi.21671. Epub 2012 Aug 31.

Loss of power in two-stage residual-outcome regression analysis in genetic association studies

Ronglin Che  1 , Alison A Motsinger-Reif, Chad C Brown
Affiliations
Comment

Loss of power in two-stage residual-outcome regression analysis in genetic association studies

Ronglin Che et al. Genet Epidemiol. 2012 Dec.
No abstract available

Keywords: degrees of freedom; loss of power; two-stage regression.

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Conflict of interest statement

The authors have no conflicts of interest to declare.

Figures

Fig. 1
Fig. 1
A comparison of test statistics (F̂ and F̂*) and parameters (F and F*) in multiple linear regression (MLR) and two-stage residual-outcome regression (2SR) across 1,000 replicates. ( RSC2 is the mean of RSC2 for each row, across all replicates.)
Fig. 2
Fig. 2
A comparison of multiple linear regression (MLR) and two-stage residual-outcome regression (2SR) analysis in terms of power across 100,000 replicates with 20 covariates and sample size of 500.
Fig. 3
Fig. 3
Power of multiple linear regression (MLR) and two-stage residual-outcome regression (2SR) analysis in a simulated example with 1 SNP + 3 confounders + 3 covariates. ( RSC2 is the mean of RSC2 for each row, across all replicates.)
See this image and copyright information in PMC

Comment on

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