metasens (version 1.5-3)

print.summary.copas: Print detailed results of Copas selection model

Description

Print method for objects of class summary.copas.

This function prints the following information:

Range of gamma0 values used (see help(copas));

Range of gamma1 values used (see help(copas));

Largest SE of all studies in meta-analysis;

Range of probability publishing trial with largest SE;

The next table gives details relating to the summary of the contour plot. Specifically, it gives details from fitting a straight line to each treatment-contour in the contour plot. Column 1 (headed level) shows the treatment-contours; column 2 (nobs) shows the number of observations used by the contour plot command within the copas function to plot this contour line; column 3 (adj.r.square) shows the adjusted r-square from fitting a straight line to this contour; columns 4 & 5 show the slope and its standard error from fitting a straight line to this contour.

Next, the printout of summary.copas is shown.

Usage

# S3 method for summary.copas
print(
  x,
  backtransf = x$backtransf,
  legend = TRUE,
  digits = gs("digits"),
  digits.se = gs("digits.se"),
  ...
)

Arguments

x

An object of class summary.copas.

backtransf

A logical indicating whether results should be back transformed in printouts and plots. If backtransf = TRUE (default), results are printed as odds ratios rather than log odds ratio, for example.

legend

A logical indicating whether a legend should be printed.

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.

...

Additional arguments (passed on to print.copas).

Author

James Carpenter , Guido Schwarzer

See Also

copas, plot.copas, summary.copas

Examples

data(Fleiss1993bin, package = "meta")

# Perform meta analysis, effect measure is odds ratio (OR)
#
m1 <- metabin(d.asp, n.asp, d.plac, n.plac, data=Fleiss1993bin, sm="OR")

# Print summary of Copas analysis
#
summary(copas(m1), level = 0.95)