plot_messi {messi}

Forestplot to Summarize Estimation and Inference on alpha_a and beta_m.

Description

Forestplot to Summarize Estimation and Inference on alpha_a and beta_m.

Usage

plot_messi(n, alpha.a.hat, beta.m.hat, labels, asym.var.mat)

Arguments

n

Sample size of the analysis

alpha.a.hat

Estimate of alpha_a, a (p_m x 1) vector.

beta.m.hat

Estimate of beta_m, a (p_m x 1) vector.

labels

A (p_m x 1) vector of mediator names. Make sure that the labels are in the same order as the mediators appear in the design matrix.

asym.var.mat

Joint asymptotic variance-covariance matrix of alpha_a and beta_m, a (2p_m x 2p_m) matrix.

Value

Data frames and forestplots summarizing alpha_a and beta_m estimation.

Examples

data(Med)

Y = Med$Y
M = Med$M
A = Med$A
C = Med$C
T.hat.external = Med$T.hat.external
var.T.hat.external = Med$var.T.hat.external

test <- messi(Y = Y, M = M, A = A, C = C, method = 'Unconstrained', T.hat.external = T.hat.external,
              var.T.hat.external = var.T.hat.external, s2.fixed = NULL)

n = Med$n
p = Med$p

plot_messi(n = n, alpha.a.hat = test$alpha.a.hat, beta.m.hat = test$beta.m.hat, 
           labels = paste0("M",1:p), asym.var.mat = test$asym.var.mat)