netmetareg: Network meta-regression with a single continuous or binary...

In guido-s/netmeta: Network Meta-Analysis using Frequentist Methods

Network meta-regression with a single continuous or binary covariate

Description

Network meta-regression with a single continuous or binary covariate for objects of class netmeta. This is a wrapper function for the R function rma.mv in the R package metafor (Viechtbauer 2010).

Usage

## S3 method for class 'netmeta'
netmetareg(
  x,
  covar = NULL,
  consistency = TRUE,
  assumption = "independent",
  method.tau = if (!x$random) "FE" else "REML",
  level = x$level.ma,
  reference.group = x$reference.group,
  nchar.trts = x$nchar.trts,
  ...
)

netmetareg(x, ...)

## Default S3 method:
netmetareg(x, ...)

## S3 method for class 'netmetareg'
print(
  x,
  digits = gs("digits"),
  digits.se = gs("digits.se"),
  digits.stat = gs("digits.stat"),
  digits.pval = gs("digits.pval"),
  print.se = FALSE,
  details.methods = TRUE,
  ...
)

Arguments

x	An object of class netmeta.
covar	Continuous or binary covariate.
consistency	A logical indicating whether a consistency or inconsistency model should be assumed.
assumption	A character string indicating which assumption is done for the covariate; either "independent" or "common" (can be abbreviated).
method.tau	A character string indicating which method is used to estimate the between-study variance tau-squared. Either "FE", "REML", or "ML".
level	The level used to calculate confidence intervals for regression coefficients.
reference.group	Reference treatment.
nchar.trts	A numeric defining the minimum number of characters used to create unique treatment names.
...	Additional arguments passed to R function rma.uni.
digits	Minimal number of significant digits, see print.default.
digits.se	Minimal number of significant digits for standard errors.
digits.stat	Minimal number of significant digits for z- or t-value, see print.default.
digits.pval	Minimal number of significant digits for p-value of overall treatment effect, see print.default.
print.se	A logical specifying whether standard errors should be printed.
details.methods	A logical specifying whether details on statistical methods should be printed.

Details

This R function is a wrapper function for R function rma.mv in the R package metafor (Viechtbauer 2010).

Note, results are not back-transformed in printouts of network meta-analyses using summary measures with transformations, e.g., log risk ratios are printed instead of the risk ratio if argument sm = "RR".

Argument '...' can be used to pass additional arguments to R function rma.mv. For example, argument control to provide a list of control values for the iterative estimation algorithm. See help page of R function rma.mv for more details.

Value

An object of class c("netmetareg", "rma.mv", "rma"). Please look at the help page of R function rma.mv for more details on the output from this function.

In addition, a list .netmeta is added to the output containing the following components:

x, covar, method.tau	As defined above.
dots	Information provided in argument '...'.
call	Function call.
version	Version of R package netmeta used to create object.
version.metafor	Version of R package metafor used to create object.

Author(s)

Nana-Adjoa Kwarteng [e-mail], Guido Schwarzer [e-mail]

References

Viechtbauer W (2010): Conducting Meta-Analyses in R with the Metafor Package. Journal of Statistical Software, 36, 1–48

See Also

netmeta

Examples

data(smokingcessation)
# Add variable with (fictitious) risk of bias values
# with 1 = "low risk" and 2 = "high risk"
#
smokingcessation$rob <- rep(1:2, 12)

pw1 <- pairwise(list(treat1, treat2, treat3),
  event = list(event1, event2, event3), n = list(n1, n2, n3),
  data = smokingcessation, sm = "OR")

net1 <- netmeta(pw1, common = FALSE, ref = "A")

# Network meta-regression with continuous covariate and assumption of
# independent slopes
nr1 <- netmetareg(net1, rob)
nr1

guido-s/netmeta documentation built on June 12, 2025, 11:59 p.m.