nma.league: League Table and Heat Plot

In audrey-b/BUGSnet: Bayesian network meta-analyses in compliance with best practice and reporting guidelines

League Table and Heat Plot

Description

Produces a league table and a league heat plot that contain point estimates of relative effectiveness for all possible pairs of treatments point estimates along with 95% credible intervals obtained with the quantile method.

Usage

nma.league(
  nma,
  central.tdcy = "median",
  log.scale = FALSE,
  order = NULL,
  low.colour = "darkgoldenrod1",
  mid.colour = "white",
  high.colour = "cornflowerblue",
  cov.value = NULL,
  digits = 2
)

Arguments

nma	A BUGSnetRun object produced by running nma.run().
central.tdcy	The statistic that you want to use in order to measure relative effectiveness. The options are "mean" and "median".
log.scale	If TRUE, odds ratios, relative risk or hazard ratios are reported on the log scale. Default is FALSE.
order	A vector of strings representing the order in which to display the treatments.
low.colour	A string indicating the colour of low relative treatment effects for the heat plot (e.g relative risk of 0.5).
mid.colour	A string indicating the colour of null relative treatment effects for the heat plot (e.g relative risk of ~1.0).
high.colour	A string indicating the colour of high relative treatment effects for the heat plot (e.g relative risk of ~2.0).
cov.value	Must be specified for meta-regression. This is the value of the covariate for which to report the results.
digits	Number of digits to display after the decimal point

Value

table - A league table. Row names indicate comparator treatments.

longtable - League table in the long format.

heatplot - League heat plot, where a color scale is used to represent relative treatment effects and ** are used to highlight statistically significant differences.

See Also

nma.run, nma.rank, nma.forest

Examples

data(diabetes.sim)

diabetes.slr <- data.prep(
  arm.data = diabetes.sim, 
  varname.t = "Treatment", 
  varname.s = "Study"
)

#Random effects, consistency model.
#Binomial family, cloglog link. This implies that the scale will be the Hazard Ratio.
diabetes.re.c <- nma.model(
  data = diabetes.slr,
  outcome = "diabetes", 
  N = "n",
  reference = "Placebo",
  family = "binomial",
  link = "cloglog",
  effects = "random",
  type = "consistency",
  time = "followup"
)
 
diabetes.re.c.res <- nma.run(
  model = diabetes.re.c,
  n.adapt = 100,
  n.burnin = 0,
  n.iter = 100)

league_table <- nma.league(
  nma = diabetes.re.c.res,
  central.tdcy = "median"
)

league_table$heatplot
league_table$table
league_table$longtable

audrey-b/BUGSnet documentation built on Feb. 2, 2025, 5:10 p.m.