crossnma2netmeta: Create a netmeta object from a crossnma object
In netmeta: Network Meta-Analysis using Frequentist Methods

crossnma2netmeta

R Documentation

Create a netmeta object from a crossnma object

Description

Auxiliary function to create a netmeta object from a crossnma object

Usage

crossnma2netmeta(
  x,
  keep.samples = TRUE,
  level = gs("level"),
  level.ma = x$model$level.ma,
  reference.group = x$model$reference,
  baseline.reference = gs("baseline.reference"),
  small.values = x$model$small.values,
  all.treatments = gs("all.treatments"),
  seq = gs("seq"),
  backtransf = x$model$backtransf,
  nchar.trts = gs("nchar.trts"),
  nchar.studlab = gs("nchar.studlab")
)

Arguments

`x`	A `crossnma` object created with R package crossnma.
`keep.samples`	A logical indicating whether to keep the generated samples.
`level`	The level used to calculate confidence intervals for individual comparisons.
`level.ma`	The level used to calculate confidence intervals for network estimates.
`reference.group`	Reference treatment (first treatment is used if argument is missing).
`baseline.reference`	A logical indicating whether results should be expressed as comparisons of other treatments versus the reference treatment (default) or vice versa. This argument is only considered if `reference.group` has been specified.
`small.values`	A character string specifying whether small treatment effects indicate a beneficial (`"desirable"`) or harmful (`"undesirable"`) effect (passed on to `netrank`, can be abbreviated.
`all.treatments`	A logical or `"NULL"`. If `TRUE`, matrices with all treatment effects, and confidence limits will be printed.
`seq`	A character or numerical vector specifying the sequence of treatments in printouts.
`backtransf`	A logical indicating whether results should be back transformed in printouts and forest plots. If `backtransf = TRUE`, results for `sm = "OR"` are presented as odds ratios rather than log odds ratios, for example.
`nchar.trts`	A numeric defining the minimum number of characters used to create unique treatment names (see Details).
`nchar.studlab`	A numeric defining the minimum number of characters used to create unique study labels.

Value

A netmeta object with additional class "netmeta.crossnma".

Author(s)

Guido Schwarzer guido.schwarzer@uniklinik-freiburg.de

Examples

## Not run: 
if (requireNamespace("crossnma", quietly = TRUE)) {
library("crossnma")
# Create a JAGS model
mod <- crossnma.model(treat, id, relapse, n, design,
  prt.data = ipddata, std.data = stddata,
  reference = "A", trt.effect = "random", method.bias = "naive")
# Fit JAGS model
set.seed(1909)
fit <- crossnma(mod)

# Print results in netmeta layout
cro <- crossnma2netmeta(fit)
cro
# SUCRAs
netrank(cro)
# Rankogram
rankogram(cro)
}

## End(Not run)

netmeta documentation built on April 3, 2025, 6:12 p.m.