Skip to main content

Table 2 Summary of longitudinal sub-models with multivariate longitudinal outcomes

From: Bayesian joint modelling of longitudinal and time to event data: a methodological review

 Number of articles (%)Reference
Type of outcome
 Continuous8(36.4%)[20, 21, 28, 32, 49, 63, 82, 83]
 Rate, Ordinal, \ (or/and continuous), Continuous, Ordinal and Discretea5(22.7%)[14, 26, 34, 50, 84]
 Continues and binary2(9.1%)[36, 57]
 Continuous and ordinal3(13.6%)[29, 41, 45]
 Continuous, ordinal and binary4(18.2%)[30, 85,86,87]
Model
 GLM, Partially LMEa2(9.1%)[20, 32]
 Multivariate GLM4(18.2%)[14, 34, 36, 57]
 Multivariate mixed effect models5(22.7%)[21, 28, 63, 82, 83]
 ZAB, Proportional-odds cumulative logit modela2(9.1%)[26, 50]
 GLM and CR mixed-effects model, Mixed-effect model and CR mixed-effects model, LME and continuous latent variable model, LME and a mixed-effects beta regression model, ZOIBa5(22.7%)[29, 41, 45, 49, 84]
 MLIRT2(9.1%)[30, 86]
 MLLTM, MLTLMa2(9.1%)[85, 87]
Random effect distribution
 Normal12 (54.5%)[20, 26, 29, 30, 36, 45, 50, 82, 84,85,86,87]
 Multivariate normal7(31.8%)[14, 21, 28, 41, 49, 63, 83]
 Dirichlet process prior3(13.7%)[32, 34, 57]
Error distribution
 Normal12(63.2%)[20, 29, 30, 36, 41, 45, 49, 57, 82, 83, 85, 87]
 Multivariate normal SN4(21.1%)[14, 21, 34, 63]
 Finite mixture of normal distributions, Multivariate SN, SN/Ia3(15.7%)[28, 32, 86]
  1. aThe order of the outcomes/models/distributions have the same order as in the reference