pri_par_adjust_static: Static prior tail-adjustment

In sl4bayesmeta: Sensitivity and learning for Bayesian meta-analysis

Description

Adjusts the scale parameter of the half-normal, exponential, half-Cauchy and Lomax distributions such that the probability mass above the reference threshold equals the given tail probability. The shape parameter of the Lomax distribution is fixed at 1.

Usage

pri_par_adjust_static(UU=1, tail_prob=0.05)

Arguments

UU	reference threshold
tail_prob	probability mass of the prior above the reference threshold

Details

The condition imposed on the distribution is Pr[x > UU] = alpha, where alpha denotes the tail probability tail_prob.

To find a prior for the heterogenity standard deviation, the standard approach for outcomes on the log-odds ratio scale is to take the tail probability alpha = 5 % (tail_prob=0.05) and thresholds UU=1 or UU=2 (Spiegelhalter et al. 2004, Neuenschwander et al. 2010). For the half-normal distribution, these conditions lead to the HN(0.5) and HN(1) prior, respectively.

Value

A list of four scale parameter values (one for each prior considered):

p_HN	parameter of half-normal prior
p_EXP	parameter of exponential prior
p_HC	parameter of half-Cauchy prior
p_LMX	scale parameter for Lomax prior with shape parameter=1

References

Neuenschwander, B., Capkun-Niggli, G., Branson, M., Spiegelhalter, D. (2010). Summarizing historical information on controls in clinical trials. Clinical Trials 7(1), 5–18. https://doi.org/10.1177/1740774509356002

Spiegelhalter, D., Abrams, K., Myles, J. (2004). Bayesian Approaches to Clinical Trials and Health-Care Evaluation. John Wiley & Sons, Ltd.

See Also

pri_par_adjust_dynamic

Examples

# 5 % tail-adjustment
pri_par_adjust_static(UU=1)
pri_par_adjust_static(UU=2)

sl4bayesmeta documentation built on Feb. 18, 2020, 3:02 p.m.