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Table 1 INLA summaries for estimated posterior means of population-level parameters (together with 2.5% and 97.5% posterior quantiles) using full Laplace approximations

From: Bayesian model selection techniques as decision support for shaping a statistical analysis plan of a clinical trial: An example from a vertigo phase III study with longitudinal count data as primary endpoint

  Parameter
Model Intercept time dosagetime
Poisson, I 1.366 (1.123, 1.603) -0.051 (-0.063, -0.038) -0.130 (-0.150, -0.109)
Poisson, IS 1.638 (1.432, 1.837) -0.189 (-0.275, -0.107) -0.173 (-0.288, -0.061)
ZIP, I 1.375 (1.121, 1.620) -0.049 (-0.062, -0.036) -0.115 (-0.137, -0.093)
ZIP, IS 1.628 (1.421, 1.830) -0.209 (-0.302, -0.119) -0.198 (-0.323, -0.075)
NB, I 1.447 (1.193, 1.695) -0.069 (-0.090, -0.050) -0.127 (-0.156, -0.098)
NB, IS 1.642 (1.433, 1.840) -0.190 (-0.289, -0.101) -0.168 (-0.289, -0.049)
arcsinh, I 2.056 (1.853, 2.259) -0.067 (-0.084, -0.051) -0.074 (-0.096, -0.052)
arcsinh, IS 2.055 (1.854, 2.255) -0.068 (-0.114, -0.022) -0.073 (-0.134, -0.012)
  1. INLA posterior means and 95% credibility intervals for arcsinh-transformed outcome modeled as continuous response with Gaussian error terms.
  2. I: model with random intercept, IS: model with random intercept and slope associated with time.