print.summary.netmeta: Print detailed results of network meta-analysis
In netmeta: Network Meta-Analysis using Frequentist Methods

print.summary.netmeta

R Documentation

Print detailed results of network meta-analysis

Description

Print method for objects of class summary.netmeta.

Usage

## S3 method for class 'summary.netmeta'
print(
  x,
  sortvar,
  common = x$x$common,
  random = x$x$random,
  prediction = x$prediction,
  reference.group = x$reference.group,
  baseline.reference = x$baseline.reference,
  all.treatments = x$all.treatments,
  details = TRUE,
  nma = TRUE,
  backtransf = x$backtransf,
  nchar.trts = x$nchar.trts,
  nchar.studlab = x$nchar.studlab,
  digits = gs("digits"),
  digits.se = gs("digits.se"),
  digits.pval.Q = max(gs("digits.pval.Q"), 2),
  digits.Q = gs("digits.Q"),
  digits.tau2 = gs("digits.tau2"),
  digits.I2 = gs("digits.I2"),
  scientific.pval = gs("scientific.pval"),
  big.mark = gs("big.mark"),
  truncate,
  text.truncate = "*** Output truncated ***",
  legend = TRUE,
  warn.deprecated = gs("warn.deprecated"),
  ...
)

Arguments

`x`	An object of class `summary.netmeta`.
`sortvar`	An optional vector used to sort individual studies (must be of same length as `x$TE`).
`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.
`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.
`details`	A logical indicating whether further details for individual studies should be printed.
`nma`	A logical indicating whether summary results of network meta-analysis 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.
`nchar.studlab`	A numeric defining the minimum number of characters used to create unique study labels.
`digits`	Minimal number of significant digits, see `print.default`.
`digits.se`	Minimal number of significant digits for standard deviations and standard errors, 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.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.
`truncate`	An optional vector used to truncate the printout of results for individual studies (must be a logical vector of length corresponding to the number of pairwise comparisons `x$TE` or contain numerical values).
`text.truncate`	A character string printed if study results were truncated from the printout.
`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.

Author(s)

Guido Schwarzer guido.schwarzer@uniklinik-freiburg.de

Examples

data(smokingcessation)

# Transform data from arm-based format to contrast-based format
#
p1 <- pairwise(list(treat1, treat2, treat3),
  event = list(event1, event2, event3), n = list(n1, n2, n3),
  data = smokingcessation, sm = "OR")

# Conduct random effects network meta-analysis and print detailed
# summary
#
net1 <- netmeta(p1, common = FALSE)
summary(net1)

## Not run: 
data(Senn2013)

# Conduct common effects network meta-analysis
#
net2 <- netmeta(TE, seTE, treat1, treat2, studlab,
  data = Senn2013, sm = "MD", random = FALSE, ref = "plac")
snet2 <- summary(net2)
print(snet2, digits = 3)

# Only show individual study results for multi-arm studies
#
print(snet2, digits = 3, truncate = multiarm)

# Only show first three individual study results
#
print(snet2, digits = 3, truncate = 1:3)

# Only show individual study results for Kim2007 and Willms1999
#
print(snet2, digits = 3, truncate = c("Kim2007", "Willms1999"))

# Only show individual study results for studies starting with the
# letter "W"
#
print(snet2, ref = "plac", digits = 3,
  truncate = substring(studlab, 1, 1) == "W")

# Conduct random effects network meta-analysis
#
net3 <- netmeta(TE, seTE, treat1, treat2, studlab,
  data = Senn2013, sm = "MD", common = FALSE, ref = "plac")
print(summary(net3), digits = 3)

## End(Not run)

netmeta documentation built on May 31, 2023, 5:45 p.m.