pairs.stan_nma: Matrix of plots for a 'stan_nma' object

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

Matrix of plots for a stan_nma object

Description

A pairs() method for stan_nma objects, which calls bayesplot::mcmc_pairs() on the underlying stanfit object.

Usage

## S3 method for class 'stan_nma'
pairs(x, ..., pars, include = TRUE)

Arguments

x	An object of class stan_nma
...	Other arguments passed to bayesplot::mcmc_pairs()
pars	Optional character vector of parameter names to include in output. If not specified, all parameters are used.
include	Logical, are parameters in pars to be included (TRUE, default) or excluded (FALSE)?

Value

A grid of ggplot objects produced by bayesplot::mcmc_pairs().

Examples

## Not run: 
## Parkinson's mean off time reduction
park_net <- set_agd_arm(parkinsons,
                        study = studyn,
                        trt = trtn,
                        y = y,
                        se = se,
                        sample_size = n)

# Fitting a RE model
park_fit_RE <- nma(park_net,
                   trt_effects = "random",
                   prior_intercept = normal(scale = 100),
                   prior_trt = normal(scale = 100),
                   prior_het = half_normal(scale = 5))

# We see a small number of divergent transition errors
# These do not go away entirely when adapt_delta is increased

# Try to diagnose with a pairs plot
pairs(park_fit_RE, pars = c("mu[4]", "d[3]", "delta[4: 3]", "tau"))

# Transforming tau onto log scale
pairs(park_fit_RE, pars = c("mu[4]", "d[3]", "delta[4: 3]", "tau"),
      transformations = list(tau = "log"))

# The divergent transitions occur in the upper tail of the heterogeneity
# standard deviation. In this case, with only a small number of studies, there
# is not very much information to estimate the heterogeneity standard deviation
# and the prior distribution may be too heavy-tailed. We could consider a more
# informative prior distribution for the heterogeneity variance to aid
# estimation.

## End(Not run)

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