BMC Medical Research Methodology

Table 2 Simulation results in the absence of a terminal event

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

Scenario				DPOs based on AJ estimator^a			DPOs based on KM estimator^b
u _i	λ ₀₁	λ ₀₂	λ _c	no events	1 event	2 events	No events	1 event	2 events
Absolute bias^c
1	1	1	0.5	−0.0005	0.0004	0.0001	−0.0005	0.0008	−0.0004
1	1	2	0.5	−0.0005	0.0005	−0.0001	−0.0005	0.0011	−0.0006
Γ(0.5, 0.5)	1	1	0.5	−0.0006	0.0004	0.0002	−0.0006	0.0003	0.0003
Γ(0.5, 0.5)	1	2	0.5	−0.0006	0.0006	−0.00004	−0.0006	0.0007	−0.0001
1	1	1	2	−0.0034	0.0086	−0.0052	−0.0044	0.0102	−0.0063
1	1	2	2	−0.0057	0.0105	−0.0048	−0.0067	0.0127	−0.0066
Γ(0.5, 0.5)	1	1	2	−0.0066	0.0112	−0.0047	−0.0066	0.0088	−0.0022
Γ(0.5, 0.5)	1	2	2	−0.0113	0.0174	−0.0061	−0.0113	0.0129	−0.0016
Root Mean Squared Error (RMSE)
1	1	1	0.5	0.0282	0.0340	0.0270	0.0282	0.0347	0.0280
1	1	2	0.5	0.0282	0.0304	0.0281	0.0282	0.0328	0.0310
Γ (0.5, 0.5)	1	1	0.5	0.0260	0.0264	0.0220	0.0260	0.0284	0.0243
Γ (0.5, 0.5)	1	2	0.5	0.0260	0.0241	0.0245	0.0260	0.0268	0.0270
1	1	1	2	0.0837	0.0969	0.0733	0.0851	0.1004	0.0758
1	1	2	2	0.0840	0.0935	0.0813	0.0855	0.0997	0.0852
Γ (0.5, 0.5)	1	1	2	0.0702	0.0762	0.0606	0.0703	0.0797	0.0641
Γ (0.5, 0.5)	1	2	2	0.0695	0.0693	0.0628	0.0696	0.0753	0.0682

^a Proposed in eq.(5)
^b Proposed in eq.(6)
^c Mean differences between true values and dynamic predicted values; True values are empirical probabilities of event numbers calculated from potential event times. Dynamic predicted values are the expectations of proposed DPOs

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