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Table 4 Simulation results in the presence 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 estimatora

u i

λ 01

λ 02

λ 0 D

λ c

no events

1 event

2 events

a terminal event

Absolute biasb

 1

1

1

0.3

0.5

0.0003

− 0.00002

0.0006

−0.0008

 1

1

2

0.3

0.5

0.0003

−0.0004

0.0010

−0.0008

 Γ (0.5, 0.5)

1

1

0.3

0.5

0.0011

−0.0002

− 0.0011

0.0002

 Γ (0.5, 0.5)

1

2

0.3

0.5

0.0011

−0.0002

− 0.0010

0.0002

 1

1

1

0.3

2

−0.0025

−0.0017

0.0040

0.0002

 1

1

2

0.3

2

−0.0057

0.0088

−0.0032

0.0001

 Γ (0.5, 0.5)

1

1

0.3

2

−0.0081

0.0086

0.0055

−0.0060

 Γ (0.5, 0.5)

1

2

0.3

2

−0.0094

0.0137

0.0010

−0.0053

Root Mean Squared Error (RMSE)

 1

1

1

0.3

0.5

0.0264

0.0316

0.0241

0.0245

 1

1

2

0.3

0.5

0.0264

0.0270

0.0281

0.0245

 Γ (0.5, 0.5)

1

1

0.3

0.5

0.0261

0.0238

0.0207

0.0211

 Γ (0.5, 0.5)

1

2

0.3

0.5

0.0261

0.0214

0.0225

0.0209

 1

1

1

0.3

2

0.0724

0.0836

0.0697

0.0681

 1

1

2

0.3

2

0.0704

0.0749

0.0783

0.0687

 Γ (0.5, 0.5)

1

1

0.3

2

0.0703

0.0644

0.0526

0.0562

 Γ (0.5, 0.5)

1

2

0.3

2

0.0701

0.0609

0.0620

0.0575

  1. a Proposed in eq.(5) and eq.(7)
  2. b Mean differences between true values and dynamic predicted values; True values are empirical probabilities of event numbers calculated using potential event times. Dynamic predicted values are expectations of proposed DPOs
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BMC Medical Research Methodology

ISSN: 1471-2288

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