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. 2014 Aug 4;6:183. doi: 10.3389/fnagi.2014.00183

Table 3.

Hierarchical linear regression results.

rs7849530 Change statistics
Model AIC R2 Adj. R2 Adj. R2 change Adj. R2 change 95% CI# F change df1 df2 Sig. F Change (P-value)
1a 8463 0.360 0.352 0.352 [0.30–0.39] 47.87 8 681 3.29 × 10−61
2b 8462 0.363 0.354 0.002 [−0.001–0.013] 2.83 1 680 0.092
3c 8442 0.382 0.373 0.019 [0.004–0.043] 21.83 1 679 4.00 × 10−6
4d 8444 0.384 0.373 0.000 [−0.001–0.005] 0.788 2 677 0.455
5e 8406 0.419 0.408 0.035 [0.011–0.070] 40.798 1 676 3.14 × 10−10
a

Predictors: Constant, Intracranial Volume, Age, Education, Diagnosis, Gender, Biomarker Group.

b

Predictors: Constant, Intracranial Volume, Age, Education, Diagnosis, Gender, Biomarker Group, APOE.

c

Predictors: Constant, Intracranial Volume, Age, Education, Diagnosis, Gender, Biomarker Group, APOE, rs7849530.

d

Predictors: Constant, Intracranial Volume, Age, Education, Diagnosis, Gender, Biomarker Group, APOE, rs7849530, rs7849530 × Tau_only, rs7849530 × Both.

e

Predictors: Constant, Intracranial Volume, Age, Education, Diagnosis, Gender, Biomarker Group, eAPOE, rs7849530, rs7849530 × Tau_only, rs7849530 × Both, rs7849530 × Amyloid_only.

#

Ninety five percentage confidence interval calculated using a bootstrap procedure with 1000 replicates.