Prints summary.MetaForest object.

# S3 method for summary.MetaForest
print(x, digits, ...)

Arguments

x: an object used to select a method.
digits: minimal number of significant digits, see print.default.
...: further arguments passed to or from other methods.

Examples

# \dontshow{
set.seed(28)
data <- SimulateSMD()
mf.random <- MetaForest(formula = yi ~ ., data = data$training,
                      whichweights = "random")
print(summary(mf.random), digits = 3)
#> MetaForest results
#>                                          
#> Type of analysis:              MetaForest
#> Number of studies:             20        
#> Number of moderators:          5         
#> Number of trees in forest:     500       
#> Candidate variables per split: 2         
#> Minimum terminal node size:    5         
#> OOB prediction error (MSE):    0.200     
#> R squared (OOB):               0.494     
#> 
#> Tests for Heterogeneity: 
#>                                tau2  tau2_SE I^2    H^2   Q-test df Q_p  
#> Raw effect sizes:              0.300 0.134   73.989 3.845 72.922 19 0.000
#> Residuals (after MetaForest):  0.102 0.068   49.259 1.971 36.751 19 0.009
#> 
#> 
#> Random intercept meta-analyses:
#>                                Intercept se    ci.lb  ci.ub p    
#> Raw effect sizes:              -0.270    0.144 -0.552 0.012 0.061
#> Residuals (after MetaForest):  -0.018    0.103 -0.220 0.185 0.862
# }