Forest plot of coefficients

Usage

plotForest(beta, stders)

Arguments

beta: regression coefficients from each analysis
stders: standard errors corresponding to betas

Value

Forest plot of effect sizes and standard errors

Examples

# Generate effects
library(mvtnorm)
library(clusterGeneration )

n = 4
Sigma = cov2cor(genPositiveDefMat(n)$Sigma)
beta = t(rmvnorm(1, rep(0, n), Sigma))
stders = rep(.1, n)  

# set names
rownames(Sigma) = colnames(Sigma) = LETTERS[1:n]
rownames(beta) = names(stders) = LETTERS[1:n]

# Run random effects meta-analysis,
# account for correlation 
RE2C( beta, stders, Sigma)
#>     stat1    stat2         RE2Cp RE2Cp.twoStep QE QEp Isq
#> 1 17.2959 579.4899 7.438565e-131            NA NA  NA  NA

# Make plot
plotForest( beta, stders )