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. Author manuscript; available in PMC: 2014 Dec 30.
Published in final edited form as: J Biopharm Stat. 2013;23(6):1383–1402. doi: 10.1080/10543406.2013.834912

Table 1.

Predictive Ability of Imbalance Measurements for Power, N=300, X ~ Bimodal, (β̃tx is treatment effect in equation (2) corresponding to 80% power)

Scenario Measure Model p-value AIC Hosmer-Lemeshow p-value D
t <2E-16 1167.9 0.675 0.063
βx= 0.63β̃tx WRS 8.34E-16 1178.8 0.499 0.054
βtx = 0 KS 3.55E-12 1187.1 0.016 0.047
sAUC 2.36E-16 1168.7 0.056 0.062

t <2E-16 5401.4 0.011 0.051
βx = −0.6β̃tx WRS <2E-16 5429.1 0.744 0.047
βtx = β̃tx KS <2E-16 5465.2 0.028 0.040
sAUC <2E-16 5410.1 0.006 0.050

t <2E-16 1066.5 0.400 0.102
βx = β̃tx WRS <2E-16 1090.8 0.861 0.082
βtx = 0 KS 1.16E-15 1097.7 0.394 0.076
sAUC <2E-16 1077.0 0.054 0.094

t <2E-16 5928.3 0.060 0.109
βx = −β̃tx WRS <2E-16 6021.9 0.509 0.095
βtx = β̃tx KS <2E-16 6158.0 <0.001 0.074
sAUC <2E-16 5948.1 0.063 0.106

t <2E-16 977.5 0.679 0.229
βx = 1.5β̃tx WRS <2E-16 1019.6 0.924 0.196
βtx = 0 KS <2E-16 1052.4 0.003 0.170
sAUC <2E-16 984.5 0.862 0.224

t <2E-16 5503.1 0.619 0.194
βx = −1.5β̃tx WRS <2E-16 5722.5 0.843 0.161
βtx = β̃tx KS <2E-16 59850 <0.001 0.123
sAUC <2E-16 5576.4 <0.001 0.183