summary.stan_nma: Posterior summaries from 'stan_nma' objects

In multinma: Bayesian Network Meta-Analysis of Individual and Aggregate Data

Posterior summaries from stan_nma objects

Description

Posterior summaries of model parameters in stan_nma objects may be produced using the summary() method and plotted with the plot() method. NOTE: To produce relative effects, absolute predictions, or posterior ranks, see relative_effects(), predict.stan_nma(), posterior_ranks(), posterior_rank_probs().

Usage

## S3 method for class 'stan_nma'
summary(object, ..., pars, include, probs = c(0.025, 0.25, 0.5, 0.75, 0.975))

## S3 method for class 'stan_nma'
plot(
  x,
  ...,
  pars,
  include,
  stat = "pointinterval",
  orientation = c("horizontal", "vertical", "y", "x"),
  ref_line = NA_real_
)

Arguments

...	Additional arguments passed on to other methods
pars, include	See rstan::extract()
probs	Numeric vector of specifying quantiles of interest, default c(0.025, 0.25, 0.5, 0.75, 0.975)
x, object	A stan_nma object
stat	Character string specifying the ggdist plot stat to use, default "pointinterval"
orientation	Whether the ggdist geom is drawn horizontally ("horizontal") or vertically ("vertical"), default "horizontal"
ref_line	Numeric vector of positions for reference lines, by default no reference lines are drawn
summary	Logical, calculate posterior summaries? Default TRUE.

Details

The plot() method is a shortcut for plot(summary(stan_nma)). For details of plotting options, see plot.nma_summary().

Value

A nma_summary object

See Also

plot.nma_summary(), relative_effects(), predict.stan_nma(), posterior_ranks(), posterior_rank_probs()

Examples

## Smoking cessation

# Run smoking RE NMA example if not already available
if (!exists("smk_fit_RE")) example("example_smk_re", run.donttest = TRUE)


# Summary and plot of all model parameters
summary(smk_fit_RE)
plot(smk_fit_RE)

# Summary and plot of heterogeneity tau only
summary(smk_fit_RE, pars = "tau")
plot(smk_fit_RE, pars = "tau")

# Customising plot output
plot(smk_fit_RE,
     pars = c("d", "tau"),
     stat = "halfeye",
     ref_line = 0)

multinma documentation built on May 31, 2023, 5:46 p.m.