nmarank: Probabilities of treatment hierarchies

In esm-ispm-unibe-ch/nmarank: Complex Hierarchy Questions in Network Meta-Analysis

Description

Specifies the frequencies of hierarchies along with their estimated probabilities and the probability that a specified criterion holds.

Usage

nmarank(
  TE.nma,
  condition = NULL,
  text.condition = "",
  VCOV.nma = NULL,
  pooled,
  nsim = 10000,
  small.values
)

## S3 method for class 'nmarank'
print(
  x,
  text.condition = x$text.condition,
  nrows = 10,
  digits = gs("digits.prop"),
  ...
)

Arguments

TE.nma	Either a netmeta object or a matrix with network estimates.
condition	Defines the conditions that should be satisfied by the treatments in the network. Multiple conditions can be combined with special operators into any decision tree. See condition.
text.condition	Optional descriptive text for the condition.
VCOV.nma	Variance-covariance matrix for network estimates (only considered if argument TE.nma isn't a netmeta object).
pooled	A character string indicating whether the hierarchy is calculated for the fixed effects ("fixed") or random effects model ("random"). Can be abbreviated.
nsim	Number of simulations.
small.values	A character string specifying whether small treatment effects indicate a "good" or "bad" effect.
x	A nmarank object.
nrows	Number of hierarchies to print.
digits	Minimal number of significant digits for proportions, see print.default.
...	Additional arguments.

Details

A simulation method is used to derive the relative frequency of all possible hierarchies in a network of interventions. Users can also define the set of all possible hierarchies that satisfy a specified criterion, for example that a specific order among treatments is retained in the network and/or a treatment is in a specific position, and the sum of their frequencies constitute the certainty around the criterion.

Value

An object of class "nmarank" with corresponding print function. The object is a list containing the following components:

hierarchies	A list of the most frequent hierarchies along with their estimated probability of occurrence.
probabilityOfSelection	Combined probability of all hierarchies that satisfy the defined condition.
TE.nma, condition, VCOV.nma,	As defined above.
pooled, nsim, small.values	As defined above.

See Also

condition, netmeta

Examples

data("Woods2010", package = "netmeta")
p1 <- pairwise(treatment, event = r, n = N, studlab = author,
               data = Woods2010, sm = "OR")
net1 <- netmeta(p1, small.values = "good")

nmarank(net1, nsim = 100)

criterionA <-
 condition("sameHierarchy",
           c("SFC", "Salmeterol", "Fluticasone", "Placebo"))
nmarank(net1, criterionA, nsim = 100)

esm-ispm-unibe-ch/nmarank documentation built on Jan. 16, 2022, 6 a.m.