netmeta (version 1.2-1)

summary.netcomb: Summary method for objects of class netcomb

Description

Summary method for objects of class netcomb.

Usage

# S3 method for netcomb
summary(
  object,
  comb.fixed = object$comb.fixed,
  comb.random = object$comb.random,
  ...
)

# S3 method for summary.netcomb print( x, comb.fixed = x$comb.fixed, comb.random = x$comb.random, backtransf = x$backtransf, nchar.trts = x$nchar.trts, digits = gs("digits"), digits.zval = gs("digits.zval"), digits.pval = gs("digits.pval"), 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 netcomb.

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.

Additional arguments.

x

An object of class netcomb or summary.netcomb.

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).

digits

Minimal number of significant digits, see print.default.

digits.zval

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.

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 same elements as a netcomb object.

See Also

netcomb, discomb

Examples

Run this code
# NOT RUN {
data(Linde2016)

# Only consider studies including Face-to-face PST (to reduce
# runtime of example)
#
face <- subset(Linde2016, id %in% c(16, 24, 49, 118))

# Conduct random effects network meta-analysis
#
net1 <- netmeta(lnOR, selnOR, treat1, treat2, id,
                data = face, reference.group = "placebo",
                sm = "OR", comb.fixed = FALSE)

# Additive model for treatment components
#
nc1 <- netcomb(net1)
summary(nc1)
print(summary(nc1), digits = 2, digits.zval = 3)

# }
# NOT RUN {
# Conduct random effects network meta-analysis
#
net2 <- netmeta(lnOR, selnOR, treat1, treat2, id,
                data = Linde2016, reference.group = "placebo",
                sm = "OR", comb.fixed = FALSE)

# Additive model for treatment components
#
nc2 <- netcomb(net2)
summary(nc2)
print(summary(nc2), digits = 2, digits.zval = 3)
# }
# NOT RUN {
# }

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