Table 3 Power estimates of MB-MDR to detect the correct interacting pair (SNP1, SNP2)

From: A robustness study of parametric and non-parametric tests in model-based multifactor dimensionality reduction for epistasis detection

	Trait status		Power
g ²	Distributions	Variances	ST	WT	Rank_ST	Rank_WT	Log_ST	Log_WT	Rtn_ST	Rtn_WT
	Normal	Equal	0.400	0.046	0.367	0.001	0.377	0.039	0.378	0.041
	Normal	Unequal	0.330	0.083	0.391	0.001	0.331	0.069	0.344	0.051
	Chi-square	Equal	0.221	0.000	0.953	0.130	0.929	0.466	0.978	0.802
0.05	Chi-square	Unequal	0.317	0.005	0.511	0.002	0.402	0.012	0.578	0.135
	t-distribution	Equal	0.344	0.239	0.920	0.042	0.338	0.240	0.806	0.320
	t-distribution	Unequal	0.383	0.116	0.615	0.002	0.380	0.122	0.543	0.132
	Normal	Equal	0.950	0.634	0.952	0.087	0.959	0.626	0.958	0.650
	Normal	Unequal	0.963	0.743	0.975	0.152	0.955	0.727	0.959	0.690
	Chi-square	Equal	0.897	0.126	1.000	0.922	1.000	1.000	1.000	1.000
0.1	Chi-square	Unequal	0.938	0.350	0.989	0.255	0.975	0.548	0.991	0.884
	t-distribution	Equal	0.873	0.881	1.000	0.885	0.853	0.876	0.999	0.987
	t-distribution	Unequal	0.921	0.801	0.995	0.409	0.921	0.806	0.989	0.834

Legend Power is defined as the proportion of simulated samples of which the causal pair (SNP1, SNP2) is significant.
ST=Student’s t-test, WT=Welch’s t-test, Rank_ST (Rank_WT)=Student’s t-test (Welch’s t-test) on trait ranks, Log_ST (Log_WT)=Student’s t-test (Welch’s t-test) on log transformed trait, Rtn_ST (Rtn_WT)= Student’s t-test (Welch’s t-test) on trait rank transformed to normal.

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ISSN: 1756-0381

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