netmeta (version 3.2-0)

crossnma2netmeta: 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")
)

Value

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

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.

Author

Guido Schwarzer

See Also

netmeta

Examples

# \donttest{
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)
}
# }