netmeta (version 1.2-1)

print.netcomb: Print objects of class netcomb

Description

Print method for objects of class netcomb.

Usage

# S3 method for 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"),
  scientific.pval = gs("scientific.pval"),
  big.mark = gs("big.mark"),
  ...
)

Arguments

x

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.

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.

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.

…

Additional arguments.

See Also

netcomb, discomb, summary.netcomb

Examples

# 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)
print(nc1, digits = 2)

# }