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Table 3 Impact of study design and diagnostic method on the estimation of HI-related protection

From: Relationship between haemagglutination-inhibiting antibody titres and clinical protection against influenza: development and application of a bayesian random-effects model

Model name$ ALL DES DIAG DOR
Number of subjects 5899 5899 5899 3825
Number of flu cases 1304 1304 1304 612
Parameter Estimates*     
μ α [95% CI] 2.844 [2.25;3.36] 2.55 [1.49;3.44] 2.751 [1.79;3.75] 1.594 [1.78;6.39]
σ α [95% CI] 0.845 [0.44;1.41] 0.936 [0.49;1.56] 0.905 [0.45;1.54] 0.956 [0.23;1.88]
μ b [95% CI] 1.299 [1;1.69] 1.222 [0.8;1.77] 1.181 [0.75;1.72] -1.414 [3.59;1.37]
σ β [95% CI] 0.376 [0.1;0.76] 0.412 [0.1;0.85] 0.428 [0.14;0.83] 0.211 [0.02;0.53]
Study design a     
α co [95% CI]   0.096 [1.23;1.44]   
β co [95% CI]   -0.021 [0.79;0.78]   
α ch [95% CI]   0.577 [0.82;1.97]   
β ch [95% CI]   0.241 [0.54;1.09]   
Diagnosis b     
α ser [95% CI]    0.091 [1.57;1.54]  
β ser [95% CI]    0.131 [0.58;0.89]  
α ili [95% CI]    0.07 [1.65;1.36]  
β ili [95% CI]    0.415 [0.52;1.45]  
E[λ i] [95% CI] 0.482 [0.41;0.57] 0.5 [0.43;0.59] 0.491 [0.42;0.58] 0.505 [0.38;0.62]
E[μ i] [95% CI] 3.116 [2.93;3.26] 3.115 [2.93;3.26] 3.112 [2.94;3.26] 3.168 [2.96;3.33]
E[σ i] [95% CI] 0.752 [0.69;0.82] 0.751 [0.69;0.82] 0.751 [0.69;0.82] 0.809 [0.74;0.89]
DIC 4667.0 4670.0 4669.0 2623.0
  1. $. ALL: All datasets and no covariate, STRAIN: All datasets + 1 covariate for virus strain (reference category: type A virus), ALL_V: datasets with information on vaccination status, VAC: datasets with information on vaccination status + 1 covariate for vaccination status (reference category: vaccinated), HOB: data reported in Hobson et al. [5], no covariate
  2. * Reported values for each parameter: posterior mean value and 95% credible interval