multinma: plot_integration_error – R documentation

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plot_integration_error

Plot numerical integration error

Description

For ML-NMR models, plot the estimated numerical integration error over the entire posterior distribution, as the number of integration points increases. See (Phillippo et al. 2020; Phillippo 2019) for details.

Usage

plot_integration_error(
  x,
  ...,
  stat = "violin",
  orientation = c("vertical", "horizontal", "x", "y"),
  show_expected_rate = TRUE
)

Arguments

`x`	An object of type `stan_mlnmr`
`...`	Additional arguments passed to the `ggdist` plot stat.
`stat`	Character string specifying the `ggdist` plot stat used to summarise the integration error over the posterior. Default is `"violin"`, which is equivalent to `"eye"` with some cosmetic tweaks.
`orientation`	Whether the `ggdist` geom is drawn horizontally (`"horizontal"`) or vertically (`"vertical"`), default `"vertical"`
`show_expected_rate`	Logical, show typical convergence rate 1/N? Default `TRUE`.

Details

The total number of integration points is set by the n_int argument to add_integration(), and the intervals at which integration error is estimated are set by the int_thin argument to nma(). The typical convergence rate of Quasi-Monte Carlo integration (as used here) is 1/N, which by default is displayed on the plot output.

The integration error at each thinning interval N_thin is estimated for each point in the posterior distribution by subtracting the final estimate (using all n_int points) from the estimate using only the first N_thin points.

Value

A ggplot object.

Examples

## Plaque psoriasis ML-NMR

# Run plaque psoriasis ML-NMR example if not already available
if (!exists("pso_fit")) example("example_pso_mlnmr", run.donttest = TRUE)


# Plot numerical integration error
plot_integration_error(pso_fit)

multinma

Bayesian Network Meta-Analysis of Individual and Aggregate Data

v0.3.0

GPL-3

Authors

David M. Phillippo [aut, cre] (<https://orcid.org/0000-0003-2672-7841>)

Initial release