Network Meta-Analysis using Frequentist Methods

A comprehensive set of functions providing frequentist methods for network meta-analysis and supporting Schwarzer et al. (2015) , Chapter 8 "Network Meta-Analysis": - frequentist network meta-analysis following Rücker (2012) ; - net heat plot and design-based decomposition of Cochran's Q according to Krahn et al. (2013) ; - measures characterizing the flow of evidence between two treatments by König et al. (2013) ; - ranking of treatments (frequentist analogue of SUCRA) according to Rücker & Schwarzer (2015) ; - partial order of treatment rankings ('poset') and Hasse diagram for 'poset' (Carlsen & Bruggemann, 2014) ; (Rücker & Schwarzer, 2017) ; - split direct and indirect evidence to check consistency (Dias et al., 2010) , (Efthimiou et al., 2019) ; - league table with network meta-analysis results; - additive network meta-analysis for combinations of treatments (Rücker et al., 2019) ; - network meta-analysis of binary data using the Mantel-Haenszel or non-central hypergeometric distribution method (Efthimiou et al., 2019) ; - 'comparison-adjusted' funnel plot (Chaimani & Salanti, 2012) ; - automated drawing of network graphs described in Rücker & Schwarzer (2016) .


News

*** netmeta, version 1.0-1, 2019-01-02 ***

** User-visible changes **

  • Revision of help page examples
    • to reflect changes in netmeta, versions 0.9-8 and 1.0-0
    • to reduce runtime below 5 seconds (CRAN requirement)

*** netmeta, version 1.0-0, 2018-12-20 ***

** Major changes **

  • Orestis Efthimiou [email protected] is a new co-author of R package netmeta

  • New function netmetabin() for network meta-analysis of binary data using the Mantel-Haenszel method or the non-central hypergeometric distribution

  • New function funnel.netmeta() for 'comparison-adjusted' funnel plots

  • New function forest.netcomb() for forest plots of additive network meta-analysis

  • New functions netbind(), forest.netbind(), and print.netbind() to combine network meta-analysis objects and to generate a forest plot with results of several network meta-analyses

  • Separate Indirect from Direct Design Evidence (SIDDE) method implemented in netsplit()

  • All network comparisons can be included in a forest plot

  • Circular network graphs with minimal number of crossings available

  • Default setting for levels of confidence intervals can be specified using R function settings.meta(); the default is still 0.95, i.e., 95% confidence intervals are computed

  • New datasets: Gurusamy2011 and Dong2013

** User-visible changes **

  • netmeta():

    • new list elements:
      • 'k.trts' with number of studies evaluating a treatment
      • 'n.trts' with number of observations receiving a treatment
      • 'events.trts' with number of events observed for a treatment
      • 'n.matrix' with number of observations in direct comparisons
      • 'events.matrix' with number of events in direct comparisons
      • 'designs' with treatment designs
    • correct entry for list element 'designs' for single design
    • only print information on studies with missing treatment effect or standard error if argument 'warn' is TRUE
  • pairwise():

    • keep original order of studies
    • arguments 'event' and 'n' can be used for generic meta-analysis method based on arguments 'TE' and 'seTE'
    • argument 'n' can be used for meta-analysis with count outcomes (based on arguments 'event' and 'time')
    • infinite treatment estimates and standard errors set to NA
    • by default, do not print warnings if comparisons will not be included in network meta-analysis
  • netsplit():

    • new argument 'method' to choose approach to split direct and indirect evidence
  • forest.netmeta():

    • argument 'reference.group' can be a vector in order to include several / all network comparisons in a forest plot
    • (invisibly) returns a data frame with information used to produce the forest plot
  • forest.netsplit() and print.netsplit():

    • argument 'showall' replaced with 'show' (see help pages)
  • forest.netsplit():

    • show prediction intervals as colored bars
    • forest plot with layout 'subgroups by comparisons': omit treatment estimates in rows with prediction intervals if network estimates are also shown
  • netcomb() and discomb():

    • argument 'seq.components' replaced with 'seq.comps'
  • discomb():

    • arguments 'reference.group' and 'baseline.reference'
  • netposet():

    • allow for ties in rankings

** Bug fixes **

  • netsplit():

    • do not reorder a treatment comparison if reference treatment (argument 'reference.group') is part of a combined treatment, e.g., for reference.group = "A" and treatment comparison "A + B" vs "C", the comparison will not be reordered as "C" vs "A + B"
  • forest.netsplit():

    • show correct prediction intervals
  • netgraph():

    • arguments 'iterate' and 'allfigures' ignored if argument 'seq' is equal to "optimal"
  • netsplit():

    • consider argument 'digits' for treatment estimates, i.e., do not always round to two digits

** Internal changes **

  • netmeta():

    • keep original order of studies in list element 'data'
  • netcomb() and discomb():

    • check if argument 'sep.components' is a single character
    • similar list elements as for R objects created with netmeta(); especially matrices with all network estimates added to output, see, for example, new list elements 'TE.fixed' and 'TE.random'
  • Internal function nma.additive():

    • calculate matrices with all network estimates
  • netleague() is a generic function

  • Help pages:

    • examples added for forest.netsplit()

*** netmeta, version 0.9-8, 2018-03-23 ***

** Major changes **

  • Main function netmeta():

    • by default, results for fixed effects and random effects network meta-analysis are reported (only results for fixed effects model were reported in older versions)
    • keep dataset used to conduct network meta-analysis
    • number of events and number of observations can be provided (and are considered from R objects created with pairwise() function)
  • Function pairwise():

    • all variables from the original dataset are kept in the output dataset
  • League tables

    • show the direct treatment estimates from pairwise comparisons in the upper triangle if the table is created for a single network meta-analysis
    • report pairwise comparisons of the treatment in the row versus the treatment in the column in the lower triangle and column versus row in the upper triangle (common presentation for network meta-analyses)
  • Network graphs are much more flexible, e.g., color of lines / edges can be specified for each direct pairwise comparison

  • New function discomb() for disconnected networks sharing at least one common treatment component to apply the additive network model for combinations of treatments

  • Treatment separator (argument 'sep.trts') can be special character from regular expressions

  • Between-study variance tau-squared is reported as NA instead of 0 in networks without heterogeneity / inconsistency

** User-visible changes **

  • netmeta():

    • settings for printing of results are defined by settings.meta(), i.e., new default is to print results for both fixed effects and random effects model
    • new arguments 'event1', 'event2', 'n1', and 'n2' to provide number of events and observations for the two treatment groups
    • new argument 'keepdata' to choose whether original dataset should be part of network meta-analysis object
    • new list element 'data' to keep dataset used to conduct network meta-analysis (if argument 'keepdata' is TRUE)
  • netgraph():

    • argument 'col' can be a matrix, e.g., created with netmatrix(), to specify the color of lines / edges for each direct pairwise comparison
    • arguments 'col.points', 'cex.points', and 'pch.points' can be used to specify the color, size, and plotting symbol for each treatment separately
    • new argument 'adj' to specify the adjustment of treatment labels
    • new argument 'pos.number.of.studies' to specify the position of the number of treatments on the edges
    • (invisibly) returns a list with information on nodes and edges (position, color, etc.) used to produce the network graph
  • pairwise():

    • print correct labels in error message for studies with duplicate treatments
  • all variables from the original dataset are kept in the output dataset
  • print.netmeta():

    • print uniquely abbreviated treatment names
  • netconnection() and print.netconnection():

    • new argument 'sep.trts' to print abbreviated treatment names
  • netleague():

    • new argument 'big.mark' to specify character printed as thousands separator, e.g., big.mark = "," will result in printing of 1,000 for the number 1000
    • new argument 'text.NA' to label missing values, i.e., for pairwise comparisons without direct evidence
    • new argument 'direct' to print direct treatment estimates (if argument 'y' is not missing)
  • print.netsplit():

    • new argument 'legend' to suppress printing of the legend
  • print.summary.netcomb():

    • new arguments 'digits.tau2' and 'digits.I2'
  • New auxiliary function netmatrix() to create a matrix with additional information for pairwise comparisons (e.g., risk of bias assessment)

** Bug fixes **

  • netmeta():

    • list elements 'P.fixed' and 'P.random' contained wrong values for network meta-analyses with a single design which resulted in an error using forest.netmeta()
  • netcomb():

    • use correct between-study variance in random effects additive network meta-analysis model
    • use correct order of studies to calculate treatment estimates
    • can be used with single pairwise comparison
  • print.summary.netcomb():

    • use correct (abbreviated) names for treatment components

** Internal changes **

  • new internal functions compmatch() and compsplit() for argument 'sep.trts' taking special character from regular expression into account, e.g., sep.trts = "."

  • new internal functions bySummary() which is used in netmeta(), netmatrix(), and pairwise()

  • createC() can be used with netconnection() objects (for disconnected networks)

  • netcomb.netmeta() has been renamed to netcomb()

  • netmeta():

    • report I2 as value between 0 and 1 (instead of 0 and 100)
    • new list element 'trts' (character vector with treatment names)
  • Internal function nma.ruecker():

    • use internal function isquared() from package meta to calculate I2
  • Internal function nma.additive():

    • calcuate between-study variance tau2 and heterogeneity statistic I2
  • Internal function prcombs():

    • new argument 'seq' to order treatments

*** netmeta, version 0.9-7, 2017-12-06 ***

** Major changes **

  • Version of R package meta must be larger or equal 4.9-0

  • New function to produce forest plots with network, direct, and indirect evidence

  • New function to estimate additive network meta-analysis for combinations of treatments

  • New default in function netsplit(): treatment comparisons are selected from upper treatment estimates matrix, i.e., comparisons are "A vs B", "A vs C", and "B vs C" for treatments "A", "B", and "C" instead of "B vs A", etc.

  • Zero treatment arm variance in multi-arm studies results in a warning instead of an error message

  • League tables can be exported as CSV or Excel file

  • New argument 'backtransf' indicating whether estimates should be back-transformed in printouts and plots, e.g., to show results as odds ratios instead of log odds ratios

  • P-values can be printed in scientific notation

  • P-values equal to 0 are actually printed as "0" instead of "< 0.0001"

  • Thousands separator can be used in printouts and forest plots for large numbers

** User-visible changes **

  • new functions:

    • forest.netsplit() to produce forest plots with direct and indirect evidence
    • print.netleague() to print league table
    • treats() to create uniquely abbreviated treatment names
    • netcomb() and netcomb.netmeta() to estimate additive network meta-analysis models for combinations of treatments
    • summary.netcomb(), print.netcomb(), and print.summary.netcomb() to print (summaries of) netcomb objects
  • print.decomp.design(), print.netmeta(), print.netsplit(), and print.summary.netmeta():

    • new argument 'big.mark' to specify character printed as thousands separator, e.g., big.mark = "," will result in printing of 1,000 for the number 1000
    • new argument 'scientific.pval' to print p-values in scientific notation, e.g., 1.2345e-01 instead of 0.12345
  • netmeta():

    • new argument 'backtransf' (see above)
    • new argument 'nchar.trts' to abbreviate treatment names in printouts
  • netleague():

    • function does not print league table, but only generates it (necessary for export of league table)
    • new arguments 'bracket' and 'separator' to define layout of confidence intervals (see R function cilayout() from R package meta)
  • netsplit():

    • new argument 'upper' to specify whether lower or upper triangle of treatment estimate matrix should be used to build comparisons
    • column with comparisons added to data frames with network, direct, and indirect estimates
    • additional new arguments (see help file): 'reference.group', 'baseline.reference', 'sep.trts', 'quote'
  • netmeasures():

    • do not round results to four digits
  • print.netmeta(), print.summary.netmeta():

    • new arguments 'backtransf' and 'nchar.trts' (see above)
    • argument 'logscale' removed (replaced by argument 'backtransf')
  • Dataset Senn2013:

    • new columns 'treat1.long' and 'treat2.long' with full treatment names added
  • Help pages:

    • new help pages for forest.netsplit(), print.netleague(), and treats()
    • updated help pages for netposet() and netsplit()

** Bug fixes **

  • netsplit():

    • order of treatments in printouts corresponds to treatment comparison, e.g., "A:B" means that treatment "A" was compared with treatment "B" (and not the other way around). Side note, not sure whether this is a bug or a feature as "A:B" noted the design "comparison A and B" so far.
  • netposet():

    • function works with a ranking matrix that contains missing elements, i.e., rankings that do not include all treatments
  • netgraph():

    • areas for multi-arm studies are printed at the correct locations if argument 'start.layout' is not equal to "circle" and argument 'seq' defines a specific treatment order (this bug was introduced in netmeta, version 0.7-0)

** Internal changes **

  • chkmultiarm():

    • warning for zero treatment arm variance instead of an error
  • new internal function uppertri() to extract elements from the upper triangle of a matrix

  • new internal function treats() to abbreviate treatment names

  • new internal function nma.additive() for estimation of additive network meta-analysis models

  • new internal function createC() to create C matrix used as input to nma.additive()

  • new internal functions prcombs() and prcomps() for printing of netcomb objects

  • Internal function p.ci() replaced with formatCI() from R package meta

  • Internal function format.TE() replaced with formatN() from R package meta

*** netmeta, version 0.9-6, 2017-08-09 ***

** Major changes **

  • Prediction intervals can be calculated for treatment estimates from a network meta-analysis

  • In netmeta(), Q statistics for heterogeneity and design inconsistency are calculated according to Krahn et al. (2013); see help page of decomp.design()

  • In printouts and forest plots, the reference treatment can be considered as treatment of interest or comparator (default), i.e., either comparisons of reference vs other treatments or other treatments vs reference are reported

  • Tests for heterogeneity and design inconsistency are shown in printouts

  • A biplot can be generated to show partial ordering of treatment rankings for more than two outcomes

  • Additional checks implemented for multi-arm studies:

    • negative or zero treatment arm variances
    • duplicate treatment comparisons or incomplete sets of treatment comparisons within a study

** User-visible changes **

  • netmeta():

    • new arguments 'prediction' and 'level.predict' to calculate prediction intervals
    • list elements 'Q.heterogeneity' and 'Q.inconsistency' based on Krahn et al. (2013)
    • new list elements 'prediction', 'lower.predict', 'upper.predict', 'df.Q.heterogeneity', 'pval.Q.heterogeneity','df.Q.inconsistency', and 'pval.Q.inconsistency'
    • list element 'df' renamed to 'df.Q'
    • stop with an informative error message if (i) any treatment arm variance derived from the treatment comparison variances is negative or zero, or (ii) in case of duplicate comparisons or an incomplete set of treatment comparisons within a study
    • argument 'details.tol.multiarm' renamed to 'details.chkmultiarm'
  • netmeta(), forest.netmeta(), print.netmeta(), print.summary.netmeta(), and summary.netmeta():

    • new argument 'baseline.reference' to print results for comparisons between reference and other treatments, or vice versa
  • print.netmeta(), print.summary.netmeta(), and summary.netmeta():

    • new argument 'prediction' to print prediction intervals
  • print.summary.netmeta():

    • print information on tests for overall heterogeneity and inconsistency
  • summary.netmeta():

    • arguments 'level' and 'level.comb' removed from R function (i.e., one has to re-run the netmeta() command for confidence intervals with other coverage levels)
  • plot.netposet():

    • new argument 'plottype' to choose between scatter plot or biplot
    • new arguments to modify layout ('cex.text', 'col.text', pch, cex.points, col.points)
  • decomp.design() and netmeasures():

    • new argument 'warn' to suppress printing of warnings

** Internal changes **

  • New internal function upgradenetmeta() to add missing list elements to older netmeta objects

  • R function ci() from R package meta added to namespace

  • chkmultiarm():

    • additional checks for (i) negative and zero variances as well as (ii) duplicate treatment comparisons or incomplete sets of treatment comparisons within a study

*** netmeta, version 0.9-5, 2017-05-31 ***

** Major changes **

  • New function netleague() to print league table with network meta-analysis results

  • pairwise():

    • zero events for binary outcomes or incidence rates are handled correctly in multi-arm studies by adding an increment to all treatment arms (in older versions of netmeta inconsistent treatment effects for multi-arm studies were possible as increments were considered in individual comparisons instead of all comparisons for a multi-arm study)
    • print warning and information on treatment comparisons with missing treatment estimate or standard error
  • forest.netmeta():

    • reference group can be omitted from forest plot
    • treatments can be sorted by treatment estimate (TE), standard error (seTE), number of studies in direct comparison (k), and proportion of direct information (prop.direct)
  • netmeta():

    • additional checks for correct number of comparisons in multi-arm studies and more informative error message for uncorrect number of comparisons in multi-arm studies due to missing treatment effects or standard errors in single comparisons
    • separator used in comparison names to concatenate treatment labels can be specified by user (default: ":")
  • In decomp.design(), by default, only print designs contributing to design-specific decomposition of within-designs Q statistic

  • Input to netdistance() can be either a netmeta object or a matrix

** User-visible changes **

  • forest.netmeta():

    • new argument 'drop.reference.group'
    • argument 'sortvar' can be used in the following ways: sortvar = TE, sortvar = -TE, sortvar = seTE, sortvar = -seTE, sortvar = k, sortvar = -k, sortvar = prop.direct, sortvar = -prop.direct
  • print.decomp.design() and netheat():

    • new argument 'showall' which defaults to FALSE
  • print.summary.netmeta():

    • print number of designs
    • print preset between-study variance and corresponding information if argument 'tau.preset' is not NULL in netmeta()
  • pairwise():

    • in multi-arm studies exclude comparisons with missing sample size or standard error from calculation of pooled variance for standardized mean difference (sm = "SMD")
  • plot.netposet():

    • new default for argument 'arrows', i.e., by default, do not show arrows in scatter plot
  • print.netsplit():

    • number of studies providing direct evidence printed
  • netdistance():

    • argument name changed from 'A' to 'x' in order to reflect that input of R function can be either a netmeta object or an adjacency matrix
  • Help pages:

    • examples corrected for dataset dietaryfat
    • do not run all examples in forest.netmeta() as CRAN only allows a run time below 10 seconds for examples provided on a help page
    • R code to produce forest plot added to examples in dataset Wood2010

** Internal changes **

  • netmeta():

    • new list element 'd' with number of designs
    • new list element 'B.matrix' with the edge-vertex incidence matrix
  • summary.netmeta():

    • new list element 'd' with number of designs
    • new list element 'tau.preset'
  • netsplit():

    • new list element 'k' with number of studies providing direct evidence
  • netconnection():

    • argument checks added
    • better code documentation
  • Internal function decomp.tau():

    • detach all designs (including protuding edges)
  • New internal function createB() to calculate edge-vertex incidence matrix

  • netmeta(), netconnection(), multiarm(), and chkmultiarm():

    • use internal function createB() instead of dedicated R code
  • print.summary.netmeta(), nma.ruecker(), and decomp.tau():

    • use command pchisq(..., lower.tail = FALSE) instead of 1 - pchisq(...)

*** netmeta, version 0.9-4, 2017-04-07 ***

** Bug fix release **

  • netsplit() used wrong comparison labels if argument 'reference.group' was used in netmeta()

  • netmeasures() ignores value of argument 'reference.group' in netmeta object

*** netmeta, version 0.9-3, 2017-03-12 ***

** Major changes **

  • Calculate indirect treatment estimates based on direct evidence proportion

  • Ranking of treatments based on fixed effect model added to netrank()

  • New function netsplit() to split direct and indirect evidence

  • New functions netposet(), print.netposet(), and plot.netposet() to calculate, print and plot partial ordering of rankings

  • New function hasse() to draw Hasse diagram of partially ordered treatment rankings

  • netmeta():

    • can be used with R objects created with pairwise()
    • checks for consistency of treatment effects and variances in multi-arm studies
  • Import ginv() from R package MASS (for consistency checks)

  • Suggested packages added (for Hasse diagram):

    • hasseDiagram
    • grid
  • Bug fixes:

    • netmeta() calculates correct direct evidence estimates under random effects model (list components 'TE.direct.random', 'seTE.direct.random', ..., 'pval.direct.random'); so far results from fixed effect model have been used
    • netmeta() excludes a treatment from list component 'seq' if all comparisons containing the respecitve treatment are excluded due to missing values in treatment effect or standard error
    • netmeasures() does not result in an error if no or only one study with two treatments is available

** User-visible changes **

  • New arguments random and tau.preset in netmeasures()

  • New functions netsplit() and print.netsplit()

  • Consider ordering of treatments in netrank() which is defined by argument seq in netmeta()

  • For multi-arm studoes, calculate pooled standard deviation in pairwise() if means and standard deviations are provided and summary measure is equal to "SMD"

** Internal changes **

  • netmeta():

    • new list element 'k.direct' with number of studies in meta-analyses with direct evidence
  • nma.ruecker():

    • bug fix such that estimates from random effects model are used for direct treatment estimates if argument 'tau.direct' is larger than zero
  • nma.krahn():

    • bug fix such that use of function does not result in an error if either no or only one study with two treatments is available
  • pairwise():

    • data.frame commands use argument stringsAsFactors = FALSE
  • chkmultiarm(): new internal function to check consistency of treatment effects and variances in multi-arm studies; calls ginv() from MASS library

  • new internal function lowertri() to extract elements from the lower triangle of a matrix

*** netmeta, version 0.9-2, 2016-11-19 ***

** Major changes **

  • R package rgl moved from imported to suggested packages as
    • 3-D network plots are not essential for network meta-analysis
    • installation of netmeta package breaks under Mac OS if XQuartz is not available

** User-visible changes **

  • Help page of netgraph() updated (information on rgl package)

** Internal changes **

  • Use chkclass() from meta package to check for class membership

*** netmeta, version 0.9-1, 2016-10-13 ***

** Major changes **

  • Number of studies can be added to network graph

  • Distance matrix can be provided directly to generate network graph

  • shadowtext() from TeachingDemos package by Greg Snow added to netmeta package

  • P-scores can be printed in forest plot

** User-visible changes **

  • help page with brief overview of netmeta package added

  • netgraph():

    • new arguments to add number of studies to network graph (number.of.studies, cex.number.of.studies, col.number.of.studies, bg.number.of.studies)
    • plastic look retained for highlighted comparisons
    • new argument D.matrix to provide treatment distances directly
  • netmeta():

    • function can be used with a single pairwise comparison without resulting in an error
  • forest.netmeta():

    • argument sortvar can be equal to Pscore, "Pscore", -Pscore, or "-Pscore" to sort treatments according to ranking generated by netrank()
    • argument leftcols or rightcols can include "Pscore" to add a column with P-Scores to the forest plot
    • new arguments small.values and digits.Pscore for P-Scores
  • print.netmeta():

    • use correct layout for network meta-analysis with a single pairwise comparison
  • decomp.design(), netheat(), netmeasures():

    • print a warning and return NULL for network meta-analysis with a single design
  • netconnection():

    • print sensible error message if argument treat2 is missing or of different length than argument treat 1
  • netdistance():

    • print sensible error message if argument A is not a matrix
  • Help pages updated: decomp.design(), print.decomp.design(), netgraph(), netheat(), netmeasures()

** Internal changes **

  • New function:

    • shadowtext() to print number of studies
  • nma.ruecker():

    • keep dimension of matrices W and B.matrix for network meta-analysis with a single pairwise comparison
  • nma.krahn():

    • print a warning and return NULL for network meta-analysis with a single design
  • decomp.tau(), tau.within():

    • return NULL for network meta-analysis with a single design

*** netmeta, version 0.9-0, 2016-04-26 ***

New functions:

  • netdistance (calculate distance matrix; replacement for internal function nodedist)
  • netconnection (Get connectivity information for network)
  • print.netconnection (corresponding print function)

Internal function nodedist removed (replaced by netdistance function)

Import functions from R package rgl (for 3-D plots)

New dataset Woods2010 (use long format in pairwise function)

Function netmeta:

  • check connectivity of network and stop with informative error message if network is not fully connected
  • new list components: 'Cov.fixed' (variance-covariance matrix for fixed effect model) 'Cov.random' (variance-covariance matrix for random effects model)

Function pairwise:

  • extension to long data format (see example on help page)

Function netmeta:

  • new arguments 'dim', 'eig3', and 'zpos' to generate 3-D network plots

Function stress (used internally):

  • extension to generate 3-D network plots
  • use netdistance function instead of nodedist

Function nma.ruecker (used internally):

  • use of netmeta function does not result in an error for networks without heterogeneity / inconsistency, i.e. networks with zero degrees of freedom (e.g. a star-shaped network with only a single study for each comparison; simple example: single comparisons A-B, A-C, A-D)
  • calculate variance-covariance matrix

Function print.netrank:

  • print title of meta-analysis (if available)

Function print.summary.netmeta:

  • print "--" instead of "< 0.0001" in networks without heterogeneity / inconsistency
  • print "0" instead of "< 0.0001" if tau-squared is zero
  • print 'p-value' instead of 'p.value'

Function print.decomp.design:

  • print 'p-value' instead of 'p.value'

Help page of netmeta function:

  • more details on contrast- and arm-based data format
  • reference to book "Meta-Analysis with R" and Rücker & Schwarzer (2014) added
  • add information that hazard ratio is a possible summary measure
  • change error in description of adjustment in random effects model

Help page of netgraph function:

  • example for 3-D network plot added

Help page of netrank function:

  • reference to Rücker & Schwarzer (2015) updated

Help page of pairwise function:

  • description on use of long data format added
  • more information on additional arguments for meta-analysis functions

New help pages:

  • netconnection, print.netconnection
  • netdistance
  • Wooks2010 dataset

*** netmeta, version 0.8-0, 2015-06-26 ***

New functions netrank and print.netrank:

  • frequentist method to rank treatments in network

Function netmeta:

  • print less irritating warning if treatment comparisons are resorted (as this is more a note than a warning)

Function print.netmeta:

  • minor change in printout (old: "Data utilised in network meta-analysis ..."; new: "Results ...")

Help pages:

  • new help page for netrank function
  • reference Rücker & Schwarzer (2015) added in help page of netgraph function
  • link to pairwise function added in help page of netmeta function

*** netmeta, version 0.7-0, 2015-02-04 ***

Version of R package meta must be larger or equal 4.0-0

Title of R package changed.

New function pairwise:

  • transforms data that are given in an arm-based format (e.g. input for WinBUGS is of this format) to contrast-based format that can be read by function netmeta

New datasets:

  • dietaryfat (dataset with incidence rates as outcomes)
  • parkinson (continuous outcomes)
  • smokingcessation (binary outcomes)

Function netmeta:

  • implement a general check for correct number of comparisons for multi-arm studies
  • use setseq function to check and set value of argument 'seq'
  • use setref function to check and set value of argument 'reference.group'
  • use chklevel function from R package meta to check levels of confidence intervals
  • consider attribute 'sm' from R objects generated with R function pairwise
  • function can be used for a pairwise meta-analysis (bug fix in nma.ruecker function used internally)

Function netgraph:

  • check that matrix 'thickness' (if provided) has same row and column names as argument 'labels'
  • use setseq function to check and set value of argument 'seq'
  • stop with an error message if argument 'seq' or 'labels' is NULL

Function netheat:

  • no net heat plot produced if (i) the number of designs is equal or smaller than 2 or (ii) no between-design heterogeneity exists
  • unintentional warnings omitted

Function forest.netmeta:

  • print a warning that the first treatment is used as reference if the reference group is unspecified instead of producing an error
  • use setseq function to check and set value of argument 'seq'
  • use setref function to check and set value of argument 'reference.group'

Function print.summary.netmeta:

  • print "." instead of "0" or "1" for diagonal elements of treatment effect and confidence interval matrices
  • print "." instead of "0" or "1" for reference group (if provided)
  • use setref function to check and set value of argument 'reference.group'
  • use is.relative.effect function from R package meta to check if a relative effect measure is used (argument 'sm')

Function print.netmeta:

  • use setref function to check and set value of argument 'reference.group'
  • use is.relative.effect function from R package meta to check if a relative effect measure is used (argument 'sm')

Function summary.netmeta:

  • use setref function to check and set value of argument 'reference.group'

Function decomp.tau and tau.within (used internally):

  • bug fix such that no error is produced in decomp.design and netheat function for networks without heterogeneity and inconsistency

Function print.decomp.design:

  • omit printing of information on between-designs Q statistic after detaching of single designs if no between-design heterogeneity exists
  • use format.tau function from R package meta to print "0" instead of "< 0.0001" if tau-squared is zero

New functions (used internally):

  • setseq - check and set argument 'seq' (and argument 'sortvar' in forest.meta function)
  • setref - check and set argument 'reference.group'
  • chklist - check for a list

New help pages for function pairwise and datasets dietaryfat, parkinson, and smokingcessation.

*** netmeta, version 0.6-0, 2014-07-29 ***

Function netgraph:

  • complete rewrite of this function (without changing previous default settings substantially)
  • list of major new features:
  • additional layouts beside circular presentation (see argument 'start.layout')
  • implementation of stress majorization algorithm to optimize layout (argument 'iterate')
  • additional methods to determine width of lines connecting treatments (argument 'thickness')
  • highlight multi-arm studies (arguments 'multiarm' and 'col.multiarm')
  • possibility to provide a neighborhood matrix to specify neighborhood differently than using the adjacency matrix, for example content-based (argument 'N.matrix')
  • possibility to provide x- and y-coordinates for network plot (arguments 'xpos' and 'ypos')

Function netmeta:

  • calculate treatment estimates from all direct pairwise treatment comparisons (both fixed effect and random effects model)
  • new list components: 'tau.preset', 'TE.direct.fixed', 'seTE.direct.fixed', 'lower.direct.fixed', 'upper.direct.fixed', 'zval.direct.fixed', 'pval.direct.fixed', 'TE.direct.random', 'seTE.direct.random', 'lower.direct.random', 'upper.direct.random', 'zval.direct.random', 'pval.direct.random'

Function nma.ruecker (used internally)

  • changed accordingly to reflect changes in netmeta function

Function forest.netmeta:

  • new argument sortvar (default: sort treatment effect estimates according to list component 'seq' of netmeta object)

New functions stress and nodedist (used internally)

  • auxiliary functions for netgraph function

Help pages updated accordingly

*** netmeta, version 0.5-0, 2014-06-24 ***

Functions nma.krahn, netmeasures, netheat, decomp.design, and print.decomp.design:

  • random effects network meta-analysis added

Function netheat:

  • new argument 'random'

Functions nma.krahn, decomp.design, and netheat:

  • new argument 'tau.preset'

Function decomp.design:

  • correct design-specific decomposition of Q statistic in network meta-analysis with multi-arm studies
  • list component 'Q.design' renamed to 'Q.het.design'
  • list component 'Q.detach' renamed to 'Q.inc.detach'
  • list component 'residuals' renamed to 'residuals.inc.detach'
  • new list components: 'Q.inc.random', 'Q.inc.random.preset', 'Q.inc.design.random.preset', 'residuals.inc.detach.random.preset', 'tau.preset'

New functions tau.within and decomp.tau (used internally)

Help pages updated accordingly

*** netmeta, version 0.4-4, 2014-05-27 ***

Functions netmeta and nma.ruecker:

  • modified such that the estimated tau-squared in random effects model considers multi-arm studies

Function print.netmeta:

  • information on percentage weight not printed as interpretation is difficult

Dataset Senn2013:

  • use of unpooled standard error for each treatment comparison

*** netmeta, version 0.4-3, 2014-04-14 ***

Function netmeta:

  • numeric values for arguments 'treat1' and 'treat2' not converted to character values (only factors converted to characters)
  • check whether treatments are different (arguments 'treat1' and 'treat2')

Function print.summary.netmeta:

  • print random effects estimates according to argument 'seq'

Function forest.netmeta:

  • sort treatment effect estimates according to argument 'seq'

Function nma.ruecker (used internally):

  • changed such that all treatment effects are calculated irregardless of treatment order (some treatment effects remained NA depending on order of treatments)

*** netmeta, version 0.4-2, 2014-03-31 ***

Function netmeasures:

  • bug fix using correct formula to calculate direct evidence proportion (variance instead of standard error)

*** netmeta, version 0.4-1, 2014-03-21 ***

Function netmeta:

  • Argument 'seq' added (see also R function netgraph)

Function netgraph:

  • new default for argument 'seq'

Help pages updated accordingly

Some internal code cleaning to improve readability of R functions

*** netmeta, version 0.4-0, 2014-03-07 ***

New functions added:

  • netgraph (network graph)
  • netheat (net heat graph)
  • netmeasures (measures for network meta-analysis)
  • decomp.design (design-based decomposition of Cochran's Q)
  • print.decomp.design (corresponding print function)
  • p.ci, format.TE, nma.krahn, nma.ruecker (used internally)

Function netmeta:

  • Check added whether all pairwise comparisons are provided for multi-arm studies

Help pages added for new functions

Help page of function netmeta updated

*** netmeta, version 0.3-1, 2013-08-01 ***

Functions netmeta and summary.netmeta:

  • new list component 'n' (number of treatments)

Function print.summary.netmeta:

  • modified such that number of treatments is printed
  • modified such that argument 'reference.group' works as expected for random effects model

*** 2013-07-24, version 0.3-0 ***

** First version released on CRAN **

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("netmeta")

1.1-0 by Guido Schwarzer, 4 months ago


https://github.com/guido-s/netmeta http://meta-analysis-with-r.org


Browse source code at https://github.com/cran/netmeta


Authors: Gerta Rücker [aut] , Ulrike Krahn [aut] , Jochem König [aut] , Orestis Efthimiou [aut] , Guido Schwarzer [aut, cre]


Documentation:   PDF Manual  


Task views: Meta-Analysis


GPL (>= 2) license


Imports magic, MASS, ggplot2

Depends on meta

Suggests colorspace, rgl, hasseDiagram, grid


Imported by NMAoutlier.

Suggested by nmadb.


See at CRAN