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.
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
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)
)
#> Warning: The largest R-hat is 1.12, indicating chains have not mixed.
#> Running the chains for more iterations may help. See
#> https://mc-stan.org/misc/warnings.html#r-hat
#> Warning: Bulk Effective Samples Size (ESS) is too low, indicating posterior means and medians may be unreliable.
#> Running the chains for more iterations may help. See
#> https://mc-stan.org/misc/warnings.html#bulk-ess
#> Warning: Tail Effective Samples Size (ESS) is too low, indicating posterior variances and tail quantiles may be unreliable.
#> Running the chains for more iterations may help. See
#> https://mc-stan.org/misc/warnings.html#tail-ess
#> Final MCMC sample equivalent to less than 1000 independent draws.
#> Please consider increasing the MCMC simulation size.
## Recover user set sampling defaults
options(.user_mc_options)