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. Author manuscript; available in PMC: 2019 Apr 1.
Published in final edited form as: Clin Nutr. 2018 Mar 12;38(2):767–773. doi: 10.1016/j.clnu.2018.03.002

Table 3.

Model-fitting results for univariate models, and proportions of variance (parameter estimates) explained by additive genetic influences (A), shared-environmental (C) and residual variation (E) with 95% confidence intervals (CI).

Goodness-of-fit index Parameter estimates (CI = 95%)

Model 2LL df AIC ΔX2 Δdf p A C/D E
Breakfast timing ACE 258.11 101 56.11 - 0.53 (0, 0.74) 0.02 (0, 0.59) 0.45 (0.26, 0.74)
AE 258.12 102 54.12 0.003 1 .954 0.56 (0.28, 0.74) -- 0.44 (0.26, 0.72)
CE 259.78 102 55.78 1.67 1 .196 1
E 271.01 103 65.01 12.89 1 < .001 1

Lunch timing ADE 155.69 101 −46.31 0.21 (0, 0.62) 0.19 (0, 0.63) 0.60 (0.37, 0.92)
AE 155.74 102 −48.26 0.05 1 .830 0.38 (0.07, 0.62) -- 0.62 (0.38, 0.93)
E 161.46 103 −44.54 5.72 1 .017 1

Dinner timing ACE 205.29 101 3.29 - 0 (0, 0.60) 0.39 (0, 0.60) 0.61 (0.37, 0.86)
AE 206.97 102 2.97 1.68 1 .195 1
CE 205.29 102 1.29 < 0.01 1 1 -- 0.39 (0.14, 0.59) 0.61 (0.40, 0.86)
E 214.17 103 8.17 8.88 1 .003 1

Midpoint of food intake ADE 168.56 101 −33.44 0.57 (0, 0.79) 0.07 (0, 0.85) 0.36 (0.21, 0.60)
AE 168.57 102 −35.43 0.008 1 .930 0.64 (0.40, 0.79) -- 0.36 (0.21, 0.60)
E 187.79 103 −18.21 19.225 1 <.0001 - - 1

Wake timing ACE 299.92 101 97.92 - 0.34 (0, 0.72) 0.20 (0, 0.64) 0.46 (0.27, 0.73)
AE 300.17 102 96.17 0.25 1 .618 0.55 (0.29, 0.73) -- 0.45 (0.27, 0.70)
CE 300.64 102 96.64 0.72 1 .395 1
E 314.24 103 108.24 14.08 1 < .001 1

Bed timing ADE 287.83 101 85.83 0 (0, 0.61) 0.42 (0, 0.65) 0.58 (0.35, 0.91)
AE 288.44 102 84.44 0.61 1 .436 0.38 (0.06, 0.63) -- 0.62 (0.37, 0.94)
E 293.80 103 87.80 5.36 1 .021 1

Chronotype ACE 729.27 101 527.27 - 0.38 (0, 0.64) 0.04 (0, 0.55) 0.58 (0.35, 0.88)
AE 729.28 102 525.28 0.01 1 .922 0.43 (0.13, 0.64) -- 0.57 (0.35, 0.86)
CE 729.90 102 525.90 0.62 1 .430 1
E 736.99 103 530.99 7.09 1 .008 1

2LL: twice negative log-likelihood; df: degrees of freedom; AIC: Akaike Information Criterion; ΔX2: difference in X2 to full model; Δdf: difference in degrees of freedom to full model. Bold values indicate best fitting model.