netmeta (version 1.2-1)

summary.netmeta: Print and summary method for objects of class netmeta

Description

Print and summary method for objects of class netmeta.

Usage

# S3 method for netmeta
summary(
  object,
  comb.fixed = object$comb.fixed,
  comb.random = object$comb.random,
  prediction = object$prediction,
  reference.group = object$reference.group,
  baseline.reference = object$baseline.reference,
  all.treatments = object$all.treatments,
  ...
)

# S3 method for summary.netmeta print( x, comb.fixed = x$comb.fixed, comb.random = x$comb.random, prediction = x$prediction, reference.group = x$reference.group, baseline.reference = x$baseline.reference, all.treatments = x$all.treatments, backtransf = x$backtransf, nchar.trts = x$nchar.trts, header = TRUE, digits = gs("digits"), digits.pval.Q = max(gs("digits.pval.Q"), 2), digits.Q = gs("digits.Q"), digits.tau2 = gs("digits.tau2"), digits.tau = gs("digits.tau"), digits.I2 = gs("digits.I2"), scientific.pval = gs("scientific.pval"), big.mark = gs("big.mark"), text.tau2 = gs("text.tau2"), text.tau = gs("text.tau"), text.I2 = gs("text.I2"), ... )

Arguments

object

An object of class netmeta.

comb.fixed

A logical indicating whether results for the fixed effects (common effects) model should be printed.

comb.random

A logical indicating whether results for the random effects model should be printed.

prediction

A logical indicating whether prediction intervals should be printed.

reference.group

Reference treatment.

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.

all.treatments

A logical or "NULL". If TRUE, matrices with all treatment effects, and confidence limits will be printed.

Additional arguments.

x

An object of class summary.netmeta.

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.

header

A logical indicating whether information on title of meta-analysis, comparison and outcome should be printed at the beginning of the printout.

digits

Minimal number of significant digits, see print.default.

digits.pval.Q

Minimal number of significant digits for p-value of heterogeneity tests, see print.default.

digits.Q

Minimal number of significant digits for heterogeneity statistics, see print.default.

digits.tau2

Minimal number of significant digits for between-study variance, see print.default.

digits.tau

Minimal number of significant digits for square root of between-study variance, see print.default.

digits.I2

Minimal number of significant digits for I-squared statistic, see print.default.

scientific.pval

A logical specifying whether p-values should be printed in scientific notation, e.g., 1.2345e-01 instead of 0.12345.

big.mark

A character used as thousands separator.

text.tau2

Text printed to identify between-study variance \(\tau^2\).

text.tau

Text printed to identify \(\tau\), the square root of the between-study variance \(\tau^2\).

text.I2

Text printed to identify heterogeneity statistic I\(^2\).

Value

A list is returned with the following elements:

comparison

Results for pairwise comparisons (data frame with columns studlab, treat1, treat2, TE, seTE, lower, upper, z, p).

comparison.nma.fixed

Results for pairwise comparisons based on fixed effects model (data frame with columns studlab, treat1, treat2, TE, seTE, lower, upper, z, p, leverage).

comparison.nma.random

Results for pairwise comparisons based on random effects model (data frame with columns studlab, treat1, treat2, TE, seTE, lower, upper, z, p).

fixed

Results for fixed effects model (a list with elements TE, seTE, lower, upper, z, p).

random

Results for random effects model (a list with elements TE, seTE, lower, upper, z, p).

predict

Prediction intervals (a list with elements seTE, lower, upper).

studies

Study labels coerced into a factor with its levels sorted alphabetically.

narms

Number of arms for each study.

k

Total number of studies.

m

Total number of pairwise comparisons.

n

Total number of treatments.

d

Total number of designs (corresponding to the unique set of treatments compared within studies).

Q

Overall heterogeneity / inconsistency statistic.

df.Q

Degrees of freedom for test of heterogeneity / inconsistency.

pval.Q

P-value for test of heterogeneity / inconsistency.

I2, lower.I2, upper.I2

I-squared, lower and upper confidence limits.

tau

Square-root of between-study variance.

Q.heterogeneity

Overall heterogeneity statistic.

df.Q.heterogeneity

Degrees of freedom for test of overall heterogeneity.

pval.Q.heterogeneity

P-value for test of overall heterogeneity.

Q.inconsistency

Overall inconsistency statistic.

df.Q.inconsistency

Degrees of freedom for test of overall inconsistency.

pval.Q.inconsistency

P-value for test of overall inconsistency.

sm

A character string indicating underlying summary measure.

method

A character string indicating which method is to be used for pooling of studies.

level

The level used to calculate confidence intervals for individual studies.

level.comb

The level used to calculate confidence intervals for pooled estimates.

comb.fixed, comb.random

As defined above.

prediction, level.predict

As defined above.

reference.group, baseline.reference

As defined above.

all.treatments, backtransf

As defined above.

ci.lab

Label for confidence interval.

seq

A character specifying the sequence of treatments.

tau.preset

An optional value for the square-root of the between-study variance \(\tau^2\).

sep.trts

A character used in comparison names as separator between treatment labels.

nchar.trts

A numeric defining the minimum number of characters used to create unique treatment names.

title

Title of meta-analysis / systematic review.

call

Function call.

version

Version of R package netmeta used to create object.

See Also

netmeta

Examples

Run this code
# NOT RUN {
data(Senn2013)

# Conduct fixed effects network meta-analysis
#
net1 <- netmeta(TE, seTE, treat1, treat2, studlab,
                data = Senn2013, sm = "MD",
                comb.random = FALSE)
print(net1, ref = "plac", digits = 3)
summary(net1)

# }
# NOT RUN {
# Conduct random effects network meta-analysis
#
net2 <- netmeta(TE, seTE, treat1, treat2, studlab,
                data = Senn2013, sm = "MD",
                comb.fixed = FALSE)
print(net2, ref = "plac", digits = 3)
summary(net2)
# }
# NOT RUN {
# }

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