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messi
This R
package fits the hard constraint, soft
constraint, and unconstrained models in Boss et al. (2023) for mediation
analyses with external summary-level information on the total
effect.
If the devtools package is not yet installed, install it first:
install.packages('devtools')
# install the package from Github:
::install_github('umich-cphds/messi') devtools
Once installed, load the package:
library(messi)
For this example, we simulate data and test the cases of null and non-null mediation effect.
library(MASS)
set.seed(20230419)
<- 500
n <- 20
p <- rnorm(n = n, mean = 0, sd = 1)
Y <- mvrnorm(n = n, mu = rep(0, p), Sigma = diag(1, p))
M <- rnorm(n = n, mean = 0, sd = 1)
A <- NULL
C <- "Unconstrained"
method <- NULL
s2.fixed <- NULL
T.hat.external <- NULL
var.T.hat.external
<- messi(Y = Y, M = M, A = A, C = C, method = method, T.hat.external = T.hat.external,
test var.T.hat.external = var.T.hat.external, s2.fixed = s2.fixed)
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$asym.var.mat)
set.seed(20230419)
<- 500
n <- 20
p <- rnorm(n = n, mean = 0, sd = 1)
Y <- mvrnorm(n = n, mu = rep(0, p), Sigma = diag(1, p))
M <- rnorm(n = n, mean = 0, sd = 1)
A <- NULL
C <- "Hard"
method <- NULL
s2.fixed <- 0
T.hat.external <- NULL
var.T.hat.external
<- messi(Y = Y, M = M, A = A, C = C, method = method, T.hat.external = T.hat.external,
test var.T.hat.external = var.T.hat.external, s2.fixed = s2.fixed)
plot_messi(n = n, alpha.a.hat = test$alpha.a.hat, beta.m.hat = test$beta.m.hat, labels = paste0("M",1:p), asym.var.mat = test$asym.var.mat)
set.seed(20230419)
<- 500
n <- 20
p <- rnorm(n = n, mean = 0, sd = 1)
Y <- mvrnorm(n = n, mu = rep(0, p), Sigma = diag(1, p))
M <- rnorm(n = n, mean = 0, sd = 1)
A <- NULL
C <- "Soft EB"
method <- NULL
s2.fixed <- 0
T.hat.external <- 0.2
var.T.hat.external
<- messi(Y = Y, M = M, A = A, C = C, method = method, T.hat.external = T.hat.external,
test var.T.hat.external = var.T.hat.external, s2.fixed = s2.fixed)
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$asym.var.mat)
set.seed(20230419)
<- 500
n <- 20
p <- rnorm(n = n, mean = 0, sd = 1)
Y <- mvrnorm(n = n, mu = rep(0, p), Sigma = diag(1, p))
M <- rnorm(n = n, mean = 0, sd = 1)
A <- NULL
C <- "Soft Fixed"
method <- 1
s2.fixed <- 0
T.hat.external <- 0.2
var.T.hat.external
<- messi(Y = Y, M = M, A = A, C = C, method = method, T.hat.external = T.hat.external,
test var.T.hat.external = var.T.hat.external, s2.fixed = s2.fixed)
plot_messi(n = n, alpha.a.hat = test$alpha.a.hat, beta.m.hat = test$beta.m.hat, labels = paste0("M",1:p), asym.var.mat = test$asym.var.mat)
data(Med)
= Med$Y
Y = Med$M
M = Med$A
A = Med$C
C = Med$T.hat.external
T.hat.external = Med$var.T.hat.external
var.T.hat.external
<- messi(Y = Y, M = M, A = A, C = C, method = 'Unconstrained', T.hat.external = T.hat.external,
test var.T.hat.external = var.T.hat.external, s2.fixed = NULL)
= Med$n
n = Med$p
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)
<- messi(Y = Y, M = M, A = A, C = C, method = 'Hard', T.hat.external = T.hat.external,
test var.T.hat.external = var.T.hat.external, s2.fixed = NULL)
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.