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Table 1 Estimated cut-points when (k1, k2, a) equals (− 2, 2, 0) in simulation data

From: A novel approach to determine two optimal cut-points of a continuous predictor with a U-shaped relationship to hazard ratio in survival data: simulation and application

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

0.60

0.06

0.77

0.00

−0.02

0.84

−0.76

− 0.01

1.03

OEHR_1

−0.90

− 0.89

0.15

−0.93

− 0.93

0.16

−1.02

−1.03

0.17

OEHR_2

0.90

0.90

0.15

0.94

0.93

0.15

1.01

1.03

0.17

  1. 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