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Table 1 Summary of TDR analysis for binary genotypes and covariates

From: Application of two machine learning algorithms to genetic association studies in the presence of covariates

  Approach
Model Include Z Stratify by Z Residualize by Z Ignore Z
1. ADDITIVE +/+ +/+ +/+ +/+
2. ADDITIVE WITH CONFOUNDING ++/+ +/+ +/+ ++/++
3. ADDITIVE WITH EFFECT MEDIATOR - -/- - - -/- - - -/- - -/-
4. INTERACTION WITH MAIN EFFECTS ++/++ ++/++ ++/++ ++/++
5. INTERACTION WITH NO MAIN EFFECTS +/++ +/++ -/+ -/+
6. CONDITIONAL ASSOCIATION +/+ +/+ -/+ -/+
  1. Summary of simulation results in Figures 1 and 2: Results are given in pairs corresponding to RF and MARS respectively; a "+" indicates reasonable TDR (≥ 80%) for detecting moderate effect sizes (≥ 0.5); "++" indicates reasonable TDR (≥ 80%) for detecting small effect sizes (≥ 0.3);"-" indicates lower TDR (50% to 80%) for moderate effect sizes; and '--" indicates very low TDR (< 20%) at moderate effect sizes. Correlation between X1 and Z is fixed at 0.5 for MODEL 2.