m_inf_sgc: Optimization function for the SGC(m) prior: Adjust the prior...
In ra4bayesmeta: Reference Analysis for Bayesian Meta-Analysis

Description Usage Arguments Details Value References See Also Examples

Computes the parameter value m=m_{inf} of the SGC(m) prior, such that the relative latent model complexity (RLMC) with respect to the reference threshold is approximately rlmc. The reference threshold is chosen as the (1-alpha)-quantile of the SGC(m_{inf}) prior.

1	m_inf_sgc(rlmc, alpha=0.5)

`rlmc`	target RLMC value. Real number in (0,1).
`alpha`	determines the (1-`alpha`)-quantile of the SGC(m) prior, which is used as reference threshold. Defaults to 0.5 (i.e. the median).

See the Supplementary Material of Ott et al. (2021), Section 2.3.1, for the formulas and explanations. Note that the parameter value m_{inf} does not depend on the data set considered.

Parameter value m=m_{inf} of the SGC(m) prior. Real number > 1.

Ott, M., Plummer, M., Roos, M. Supplementary Material: How vague is vague? How informative is informative? Reference analysis for Bayesian meta-analysis. Revised for Statistics in Medicine. 2021.

M_inf_sigc

# extreme RLMC target value close to 0 used in Ott et al. (2021)
m_inf_sgc(rlmc=0.0001)

# 25% quantile instead of the median as ref. threshold
m_inf_sgc(rlmc=0.0001, alpha=0.75)