si4bayesmeta: Sensitivity and Identification for the Bayesian Meta-Analysis

Sensitivity and identification estimates for all the parameters in the Bayesian normal-normal hierarchical model (NNHM) induced by a Half-Normal (HN) and a Half-Cauchy (HC) heterogeneity priors are produced by two d2BC_S_I_HN_raw and d2BC_S_I_HC_raw functions. Six scenarios are considered: target relative latent model complexity (RLMC) values fixed at 0.25, 0.5 and 0.75 with RLMC-adjusted HN and HC heterogeneity priors. Corresponding posterior estimates can be obtained by the functions raw_estimates_HN and raw_estimates_HC. The methodology implemented in this package has been developed in Roos et al. (2020).

install.packages("si4bayesmeta", repos="http://R-Forge.R-project.org")

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