rlmc_scaling_up {si4bayesmeta} | R Documentation |
Computes RLMC-adjusted scaled study-specific within-study standard deviations of observations in the likelihood according to Roos et al. (2020). The mean of the scaled observation is assumed to be fixed at the mean of the original observation and only its standard deviation is changed.
rlmc_scaling_up(sigma, rlmc, hh)
sigma |
a vector of fixed standard deviations provided in the likelihood |
rlmc |
the original RLMC |
hh |
perturbation for RLMC |
In this function the increased impact of observations by reducing their standard deviation is implemented, which we call the 'up' case. Smaller scaled sigmai values mean that the observations are made more informative.
Scaled sigma (a vector with within-study standard deviations)
Roos, M., Hunanyan, S., Bakka, H., Rue, H., (2020). Sensitivity and identification quantification by a relative latent model complexity perturbation in the Bayesian meta-analysis. Manuscript submitted to Research Synthesis Methods.