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

Table 3.

Estimated cut-points when (k1, k2, a) equals (−4/3, 4, 1) 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 −0.08 −0.08 0.15 −0.19 −0.20 0.17 −0.51 − 0.51 0.20
OEHR_1 −0.41 −0.39 0.23 −0.45 − 0.46 0.24 − 0.60 −0.59 0.26
OEHR_2 1.49 1.49 0.08 1.51 1.52 0.08 1.55 1.55 0.10

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