Table 6 The average accuracy of the Bayesian multivariate survival tree approaches based on models 1, 2, and 3 for non-molar teeth in elderly patients with non-diabetic simulated in our simulation study.

Number of teeth per patient	% of censoring rate	Number of patients = 200			Number of patients = 500			Number of patients = 1000
Number of teeth per patient	% of censoring rate	Model 1	Model 2	Model 3	Model 1	Model 2	Model 3	Model 1	Model 2	Model 3
\(n_i=5\)	10	0.8097	0.8814	0.9357	0.8254	0.9037	0.9457	0.8386	0.9138	0.9558
	50	0.7924	0.8729	0.9249	0.8167	0.8960	0.9399	0.8279	0.9061	0.9500
	80	0.7783	0.8629	0.9050	0.7832	0.8709	0.9124	0.8014	0.8810	0.9225
\(n_i=10\)	10	0.8201	0.8963	0.9445	0.8321	0.9175	0.9530	0.8562	0.9276	0.9631
	50	0.8016	0.8864	0.9387	0.8279	0.9082	0.9494	0.8473	0.9183	0.9595
	80	0.7971	0.8754	0.9125	0.8172	0.8841	0.9204	0.8316	0.8942	0.9305
\(n_i=20\)	10	0.8354	0.9113	0.9571	0.8497	0.9246	0.9722	0.8624	0.9355	0.9832
	50	0.8219	0.9036	0.9458	0.8371	0.9157	0.9513	0.8503	0.9258	0.9614
	80	0.8193	0.8969	0.9266	0.8313	0.9072	0.9584	0.8415	0.9173	0.9685

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

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