Description Usage Arguments Note Author(s) See Also Examples
This function (1) imputes data for a metaanalytic data set with unpublished studies, then (2) generates a funnel plot.
1 2 3 4 5 6 7 8 9 10 
table 
The name of the table containing the metaanalysis data. 
binary 

mean.sd 

higher.is.better 

outlook 
If you want all unpublished studies to be assigned the same outcome, set this parameter to one of the following values: 
vpos 
The userdefined effect size for unpublished studies with a 
pos 
The userdefined effect size for unpublished studies with a 
neg 
The userdefined effect size for unpublished studies with a 
vneg 
The userdefined effect size for unpublished studies with a 
level 
The confidence level, as a percent. 
binary.measure 
The effect size measure used for binary outcomes. "RR" for relative risk; "OR" for odds ratios. 
continuous.measure 
The effect size measure used for continuous outcomes. "SMD" for standardized mean difference (with the assumption of equal variances). 
summary.measure 
The measure used for summary effect sizes. 
method 
The same parameter in the escalc() function of the metafor package. "DL" for the DerSimonianLaird method. 
random.number.seed 
Leave as 
sims 
The number of simulations to run per study when imputing unpublished studies with binary outcomes. 
smd.noise 
The standard deviation of Gaussian random noise to be added to standardized mean differences when imputing unpublished studies with continuous outcomes. 
title 
The title of the funnel plot. 
pch.pub 
The symbol used to denote a published study. 
pch.unpub 
The symbol used to denote an unpublished study. 
The function employs functions in the metafor
package: escalc()
and forest()
.
Noory Kim
1 2 3 4 5 6 7 8 
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.