asthma: Asthma exacerbation recurrent event data.

In RBesT: R Bayesian Evidence Synthesis Tools

Asthma exacerbation recurrent event data.

Description

Data set containing historical information for placebo arms of relevant trials for the treatment of asthma. The primary outcome is the rate of asthma exacerbations, a recurrent event modelled with a negative binomial distribution. The full data set as published in Holzhauer, Wang & Schmidli (2018) summarizes ten historical placebo arms by their back-calculated log mean event rate and dispersion together with the associated standard errors on the log scale.

Usage

asthma

Format

A data frame with 10 rows and 11 variables:

study

study label

NCT

ClinicalTrials.gov / ISRCTN registry identifier(s)

d

follow-up (exposure) duration in years

n

study size

mu_hat

estimated mean event rate

log_mu_hat

log mean event rate

se_log_mu_hat

standard error of the log mean event rate

kappa_hat

estimated dispersion parameter

log_kappa_hat

log dispersion parameter

se_log_kappa_hat

standard error of the log dispersion parameter

phase

development phase of the trial

References

\insertRef

holzhauer2018RBesT

Examples

## Setting up dummy sampling for fast execution of example
## Please use 4 chains and 20x more warmup & iter in practice
.user_mc_options <- options(RBesT.MC.warmup=50, RBesT.MC.iter=100,
                            RBesT.MC.chains=2, RBesT.MC.thin=1)

set.seed(34563)
asthma_ph3 <- subset(asthma, phase == "phase III")
map_asthma <- gMAP(cbind(log_mu_hat, se_log_mu_hat) ~ 1 + offset(log(d)) | study,
  family = gaussian,
  data = asthma_ph3,
  tau.dist = "HalfNormal", tau.prior = 0.5,
  beta.prior = cbind(0, 2)
)
## Recover user set sampling defaults
options(.user_mc_options)

RBesT documentation built on Sept. 18, 2026, 5:06 p.m.