as.data.frame.metabind: Coerce to a data frame

Description

The as.data.frame method returns a data frame containing information on meta-analysis results.

Usage

# S3 method for metabind
as.data.frame(
  x,
  row.names = NULL,
  optional = FALSE,
  common = !is.null(x$common),
  random = !is.null(x$random),
  prediction = !is.null(x$predict),
  subgroup = !is.null(x$subgroup),
  drop_all_NA = TRUE,
  ...
)

Value

A data frame is returned by the function as.data.frame. For subgroup results, df.Q.b is a list column containing the complete degrees of freedom for each subgroup-difference test. Element test.Q.b identifies chi-squared ("Q") and F ("F") tests; unavailable types are NA. Variance fields tau2, lower.tau2, upper.tau2,

se.tau2, tau, lower.tau, and upper.tau

are list columns containing the complete numeric vectors, including length-one vectors for single-component analyses. Component order and names are preserved. For random effects and prediction results, column interval.slot

numbers the intervals within each meta-analysis and result type. Repeated uses of the same method have different interval numbers. Together, id and interval.slot link each subgroup result to the corresponding overall result.

Arguments

x: An object of class metabind.
row.names: NULL or a character vector giving the row names for the data frame.
optional: Argument is ignored.
common: A logical indicating whether to return results for the common effect model.
random: A logical indicating whether to return results for the random effects model.
prediction: A logical indicating whether to return prediction intervals.
subgroup: A logical indicating whether to return subgroup results in addition to the overall results.
drop_all_NA: A logical indicating whether to drop variables containing only missing values.
...: Other arguments (ignored).

Author

Guido Schwarzer [email protected]

Examples

Run this code

data(Fleiss1993cont)
#
ma1 <- metacont(n.psyc, mean.psyc, sd.psyc, n.cont, mean.cont, sd.cont,
  data = Fleiss1993cont, sm = "SMD", studlab = paste(study, year))
#
ma2 <- metacont(n.psyc, mean.psyc, sd.psyc, n.cont, mean.cont, sd.cont,
  data = Fleiss1993cont, sm = "SMD", studlab = paste(study, year),
  method.smd = "glass")

mb12 <-
  metabind(ma1, ma2, name = c("Hedges' g", "Glass' delta"), common = FALSE)

as.data.frame(mb12)