View source: R/print.orbbound.R
print.orbbound | R Documentation |
Print method for objects of class orbbound
.
## S3 method for class 'orbbound' print( x, common = x$x$common, random = x$x$random, header = TRUE, backtransf = x$backtransf, digits = gs("digits"), digits.stat = gs("digits.stat"), digits.pval = max(gs("digits.pval"), 2), digits.tau2 = gs("digits.tau2"), scientific.pval = gs("scientific.pval"), big.mark = gs("big.mark"), warn.deprecated = gs("warn.deprecated"), ... )
x |
An object of class |
common |
A logical indicating whether sensitivity analysis for common effect model should be printed. |
random |
A logical indicating whether sensitivity analysis for random effects model should be printed. |
header |
A logical indicating whether information on meta-analysis should be printed at top of printout. |
backtransf |
A logical indicating whether printed results
should be back transformed. If |
digits |
Minimal number of significant digits, see
|
digits.stat |
Minimal number of significant digits for z- or
t-value, see |
digits.pval |
Minimal number of significant digits for p-value
of overall treatment effect, see |
digits.tau2 |
Minimal number of significant digits for
between-study variance, see |
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. |
warn.deprecated |
A logical indicating whether warnings should be printed if deprecated arguments are used. |
... |
Additional arguments to catch deprecated arguments. |
For summary measures 'RR', 'OR', and 'HR' column labeled maxbias
contains the relative bias, e.g. a value of 1.10 means a maximum
overestimation by 10 percent. If logscale=TRUE
for these
summary measures, maximum bias is instead printed as absolute bias.
Guido Schwarzer guido.schwarzer@uniklinik-freiburg.de
orbbound
, forest.orbbound
data(Fleiss1993bin, package = "meta") m1 <- metabin(d.asp, n.asp, d.plac, n.plac, data = Fleiss1993bin, sm = "OR") orb1 <- orbbound(m1, k.suspect = 1:5) print(orb1, digits = 2) # Print log odds ratios instead of odds ratios # print(orb1, digits = 2, backtransf = FALSE) # Assuming that studies are missing on the left side # orb1.missleft <- orbbound(m1, k.suspect = 1:5, left = TRUE) orb1.missleft m2 <- metabin(d.asp, n.asp, d.plac, n.plac, data = Fleiss1993bin, sm = "OR", method = "Inverse") orb2 <- orbbound(m2, k.suspect = 1:5) print(orb2, digits = 2)
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