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Table 5 Parameter estimates in landmarking supermodel using two-types of dynamic pseudo observations (DPOs)

From: Dynamic prediction of repeated events data based on landmarking model: application to colorectal liver metastases data

  DPOs based on AJ estimator (eq.(5)) DPOs based on KM estimator (eq.(6))
1 recurrence 2 or more recurrences 1 recurrence 2 or more recurrences
estimate robust s.e. estimate robust s.e. estimate robust s.e. estimate robust s.e.
Intercept −1.22 1.99 1.30 4.27 −1.06 1.97 −0.13 4.23
Time (year)
s 2.19 3.28 −6.24 6.28 1.92 3.24 −3.98 6.15
s2 −1.53 1.64 2.42 2.69 −1.41 1.62 1.38 2.61
s3 0.22 0.24 −0.32 0.34 0.21 0.24 −0.19 0.33
The number of recurrences (1 or more / 0)
 Intercept 1.92 2.12 0.49 4.72 1.84 2.09 1.51 4.54
s −2.87 3.26 3.36 7.01 −2.70 3.21 1.78 6.73
s2 1.65 1.55 −2.26 2.99 1.58 1.53 −1.55 2.87
s3 −0.24 0.22 0.38 0.38 −0.23 0.22 0.29 0.37
Multiple tumors / single tumor
 Intercept 4.46 2.09 −2.27 4.32 4.31 2.05 −1.30 4.44
s −7.87 3.21 3.16 6.64 −7.57 3.15 1.38 6.77
s2 3.86 1.50 −0.91 2.89 3.71 1.48 0.01 2.91
s3 −0.53 0.21 0.09 0.37 −0.51 0.21 −0.04 0.36
The length of tumor (> 2 cm / ≤2 cm)
 Intercept −0.10 1.87 −1.19 4.07 −0.09 1.89 −0.66 4.00
s 0.31 2.88 4.08 6.21 0.30 2.91 3.29 6.04
s2 −0.21 1.34 −2.05 2.70 −0.19 1.37 −1.74 2.58
s3 0.03 0.19 0.29 0.35 0.02 0.20 0.26 0.33