Table 8 Comparison the result of the average classification accuracy over 1,000 test sets of Bayesian multivariate survival trees obtained from 3 candidate models between simulation data and real dental data.

From: On a Bayesian multivariate survival tree approach based on three frailty models

Case

No. of teeth per patient

Simulation data

Real dental data

Model 1

Model 2

Model 3

Model 1

Model 2

Model 3

Diabetes and molar teeth

1-

0.7684

0.8656

0.8949

0.7764

0.8758

0.9051

6-2

0.7856

0.8764

0.9016

0.7935

0.8866

0.9118

Diabetes and non-molar teeth

15

0.7672

0.8756

0.9025

0.7854

0.8863

0.9254

610

0.7929

0.8732

0.9152

0.8163

0.8966

0.9366

11-0

0.8054

0.8737

0.9218

0.8176

0.8963

0.9354

Non-diabetic and molar teeth

15

0.7972

0.8770

0.9162

0.7983

0.8872

0.9264

6-2

0.8183

0.8873

0.9250

0.8198

0.8975

0.9352

Non-diabetic and non-molar teeth

15

0.7832

0.8709

0.9124

0.7961

0.8811

0.9226

610

0.8172

0.8841

0.9204

0.8283

0.8943

0.9306

11–20

0.8415

0.9173

0.9685

0.8471

0.9275

0.9787

  1. Bold face numbers indicate the highest classification accuracy across the three models under each scenario.
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