Bayesian Analysis of Survival Data with Missing Censoring Indicators

. Author manuscript; available in PMC: 2021 Sep 1.

Published in final edited form as: Biometrics. 2020 May 4;77(1):305–315. doi: 10.1111/biom.13280

Observation cases	Data function	Poisson Parameters
1: Q_i = 0	D_1i = 0	$τ_{1 i} = \sum_{j = 1}^{m_{i}} μ_{i j}$
2: Q_i = ζ_i = 1, Δ_i = 0	D_1i = 0, D_2i = 1	$τ_{1 i} = \sum_{j = 1}^{m_{i}} μ_{i j} + \sum_{j = 1}^{m_{i} - 1} G_{i j}$ , τ_2i = G_{im_i}
3: Q_i = ζ_i = Δ_i = 1	D_1i = 0, D_2i = 1	$τ_{1 i} = \sum_{j = 1}^{m_{i} - 1} μ_{i j} + \sum_{j = 1}^{m_{i}} G_{i j}$ , τ_2i = μ_{im_i}
4: Q_i = 1, ζ_i = 0	D_1i = 0, D_2i = 1	$τ_{1 i} = \sum_{j = 1}^{m_{i} - 1} (μ_{i j} + G_{i j})$ , τ_2i = G_{im_i} + μ_{im_i}