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. 2019 May 9;19:96. doi: 10.1186/s12874-019-0738-4

Table 2.

Estimated cut-points when (k1, k2, a) equals (−8/5, 8/3, 1/2) in simulation data

Method Pc = 0% Pc = 20% Pc = 50%
Median Mean Sim SE Median Mean Sim SE Median Mean Sim SE
Median ‘ −0.01 0.00 0.05 − 0.01 0.00 0.05 −0.01 0.00 0.05
Q1Q3_1 −0.68 −0.68 0.06 −0.68 − 0.68 0.06 − 0.68 −0.68 0.06
Q1Q3_2 0.67 0.67 0.07 0.67 0.67 0.07 0.67 0.67 0.07
MinP −0.42 −0.40 0.13 −0.47 −0.48 0.15 −0.73 − 0.74 0.16
OEHR_1 −0.58 − 0.61 0.20 −0.65 − 0.65 0.19 − 0.80 − 0.77 0.22
OEHR_2 1.17 1.18 0.11 1.21 1.21 0.10 1.30 1.29 0.13

Pc = censoring proportion; Sim SE = simulation standard error; Median ‘= using the median value of the continuous covariate as a cut-point; Q1Q3 = using the upper and lower quartiles values as cut-points, Q1Q3_1 is the upper quartile value and Q1Q3_2 is the lower quantile value; MinP = the single cut-point minimum p-value method with log-rank test; OHER = the optimal equal-HR method proposed in this study, OEHR_1 is the left estimated cut-point and OEHR_2 is the right estimated cut-point