Table 1.
Results for Binomial/logit regression of CHD on sleep EEG δ-power characteristics using six models, each model corresponds to one column
| M1 | M2 | M3 | M4 | M5 | M6 | |
|---|---|---|---|---|---|---|
| Age × 102 | 6.41(0.40) | 6.48(0.40) | 6.40(0.40) | 6.37(0.40) | 6.47(0.40) | 6.39(0.40) |
| Sex × 10 | 6.97(0.82) | 7.31(0.82) | 7.03(0.83) | 6.88(0.81) | 7.31(0.82) | 7.03(0.83) |
| Caucasian × 10 | –3.34(0.91) | –3.29(0.91) | –3.30(0.91) | –3.50(0.91) | –3.29(0.91) | –3.30(0.91) |
| BMI × 102 | 2.66(0.81) | 3.18(0.77) | 2.64(0.81) | 2.61(0.81) | 3.18(0.77) | 2.64(0.81) |
| RDI × 103 | 6.12(2.98) | 6.45(3.03) | 6.01(2.99) | 6.49(3.03) | ||
| Mean | 2.26(0.74) | 2.12(1.09) | 2.06(1.09) | |||
| Max | –1.62(0.81) | –1.81(1.01) | –1.83(1.01) | |||
| Max-mean | –2.02(0.70) | –1.93(0.97) | –1.92(0.96) | |||
| Max. loc. × 102 | 1.30(2.26) | 0.95(2.27) | 1.32(2.26) | 0.96(2.26) | ||
| Min × 10 | 2.94(6.24) | 3.75(6.26) | 4.32(5.04) | 4.81(5.04) | ||
| Min. loc. × 102 | 0.36(1.64) | 0.38(1.64) | 0.37(1.64) | 0.39(1.64) | ||
| df × 103 | –3.15(6.32) | –2.58(6.32) | –2.83(6.26) | –2.33(6.26) | ||
| df/hour × 102 | 3.88(4.40) | 4.45(4.41) | 4.15(4.34) | 4.66(4.34) |
NOTE: A missing value indicates that that particular variable is not included into the model. We show the estimated parameters and standard errors (within brackets). Covariate labels are self-explanatory with the exception of “max-mean”: the difference between maximum and mean and “df”: number of degrees of freedom.