threshold • nmareporting

library(nmareporting)

threshold analysis | arguments

posterior mean estimates
likelihood covariance matrix
posterior covariance matrix
design matrix of contrasts

threshold analysis | posterior mean estimates

# get posterior mean estimates
post_means <- 
  summary(parkinsons_nma, pars=c("d")) %>% 
  as.data.frame() %>%
  pull("mean")

# print values
post_means

threshold analysis | design matrix

threshold | posterior likelihood


Sigma_d <- 
  diag(rep(100^2, length(post_means)))