Gaussian Copula Regression Modeling for Marker Classification Metrics with Competing Risk Outcomes
Table 5
Coefficients (Coef.) and standard error (SE) of the best-fitting parametric Gaussian copula regression model considering the composite marker for the study of prostate cancer study data.
Parameter
Coef.
SE
value
0.8904
0.1054
−0.4462
0.1021
0.5164
0.0565
3.346
0.6422
0.1933
0.046
4.5952
0.4928
0.0221
0.0083
0.0077
4.1075
1.1176
0.0002
−0.0588
0.0155
0.0001
−0.85
0.2361
0.0003
−0.1895
0.0511
0.0002
−0.5973
0.0505
−0.039
0.071
0.584
0.8870
0.1053
−0.4464
0.1021
0.5193
0.0563
3.353
0.6439
0.193
0.046
4.5971
0.4917
0.0222
0.0082
0.0069
4.1287
1.1157
0.0002
−0.0591
0.0155
0.0001
−0.8564
0.236
0.0003
−0.2019
0.0454
−0.6033
0.0489
Zero
N.A.
N.A.
The model includes all the parameters on the left, whereas on the right, the parameter is set to zero.
