for the Cox (log(HR)=−0.082) and logistic (log(OR)=−0.080) regression models, but the SEs were 0.031 and 0.027, respectively. This led to a smaller P-value for the logistic regression model (P=0.003 compared with P=0.007). Again, the effect sizes of the logistic regression model tended to be larger in magnitude than those of the Cox model for the effect estimates of greater magnitude. Two examples of this are the SNPs rs9349379 (chr6:g.12903957A>G; an intronic variant in PHACTR1) and rs2075650 (chr19:g.45395619A>G; an intronic variant in TOMM40 upstream of APOE) where the effect sizes were 0.03 and 0.013 larger in magnitude for the logistic regression model compared with the Cox model. This in combination with smaller SEs for the logistic regression model led to much smaller P-values for this model (Table 3).
