netmeta (version 3.1-1)

print.netcomb: Print method for objects of class netcomb

Description

Print method for objects of class netcomb.

Usage

# S3 method for netcomb
print(
  x,
  common = x$common,
  random = x$random,
  overall.hetstat = x$overall.hetstat,
  backtransf = x$backtransf,
  nchar.comps = x$nchar.comps,
  digits = gs("digits"),
  digits.stat = gs("digits.stat"),
  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"),
  big.mark = gs("big.mark"),
  scientific.pval = gs("scientific.pval"),
  zero.pval = gs("zero.pval"),
  JAMA.pval = gs("JAMA.pval"),
  print.tau2 = gs("print.tau2"),
  print.tau = gs("print.tau"),
  print.Q = gs("print.Q"),
  print.I2 = gs("print.I2"),
  print.I2.ci = gs("print.I2.ci"),
  text.tau2 = gs("text.tau2"),
  text.tau = gs("text.tau"),
  text.I2 = gs("text.I2"),
  details.methods = gs("details"),
  legend = gs("legend"),
  warn.deprecated = gs("warn.deprecated"),
  ...
)

Arguments

x

An object of class netcomb or summary.netcomb.

common

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

random

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

overall.hetstat

A logical indicating whether to print heterogeneity measures.

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.comps

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

digits

Minimal number of significant digits, see print.default.

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.

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.

big.mark

A character used as thousands separator.

scientific.pval

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

zero.pval

A logical specifying whether p-values should be printed with a leading zero.

JAMA.pval

A logical specifying whether p-values for test of overall effect should be printed according to JAMA reporting standards.

print.tau2

A logical specifying whether between-study variance \(\tau^2\) should be printed.

print.tau

A logical specifying whether \(\tau\), the square root of the between-study variance \(\tau^2\), should be printed.

print.Q

A logical value indicating whether to print the results of the test of heterogeneity.

print.I2

A logical specifying whether heterogeneity statistic I\(^2\) should be printed.

print.I2.ci

A logical specifying whether confidence interval for heterogeneity statistic I\(^2\) should be printed.

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\(^2\).

details.methods

A logical specifying whether details on statistical methods should be printed.

legend

A logical indicating whether a legend should be printed.

warn.deprecated

A logical indicating whether warnings should be printed if deprecated arguments are used.

...

Additional arguments (to catch deprecated arguments).

Author

Guido Schwarzer

See Also

netcomb, discomb

Examples

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", common = FALSE)

# Additive model for treatment components
#
nc1 <- netcomb(net1)
nc1

# \donttest{
print(nc1, digits = 2, digits.stat = 3)

# Conduct random effects network meta-analysis
#
net2 <- netmeta(lnOR, selnOR, treat1, treat2, id,
  data = Linde2016, reference.group = "placebo",
  sm = "OR", common = FALSE)

# Additive model for treatment components
#
nc2 <- netcomb(net2)
nc2
print(nc2, digits = 2, digits.stat = 3)
# }