summary.MED {MED} | R Documentation |
Summarizing output of study.
Description
summary
method for class "MED"
Usage
## S3 method for class 'MED'
summary(object, ...)
## S3 method for class 'summary.MED'
print(x, ...)
Arguments
object |
An object of class |
x |
An object of class |
... |
Further arguments passed to or from methods. |
Details
print.summary.MED
prints a simplified output similar to print.summary.lm
. The resulting table provides the point estimates, estimated standard errors, 95% Wald confidence intervals, the Z-statistic and the P-values for a Z-test.
Value
The function summary.MED
returns a list with the following components
Estimate |
A matrix with point estimates along with standard errors, confidence intervals etc. This is the matrix users see with the |
vcov |
The variance-covariance matrix of the point estimates. |
Conv |
The convergence result of the |
weights |
The weights for each subject in each treatment arm. These are same as the |
call |
The |
Author(s)
Gary Chan
See Also
Examples
library(MED)
#binary treatment and binary mediator
set.seed(25)
n <- 200
Z <- matrix(rnorm(4*n),ncol=4,nrow=n)
prop.e <- 1 / (1 + exp(Z[,1] - 0.5 * Z[,2] + 0.25*Z[,3] + 0.1 * Z[,4]))
treat <- rbinom(n, 1, prop.e)
prop.m <- 1 / (1 + exp(-(0.5 - Z[,1] + 0.5 * Z[,2] - 0.9 *Z [,3] + Z[,4] - 1.5 * treat)))
M <- rbinom(n, 1, prop.m)
Y <- 200 + treat + M + 27.4*Z[,1] + 13.7*Z[,2] +
13.7*Z[,3] + 13.7*Z[,4] + rnorm(n)
X <- cbind(exp(Z[,1])/2,Z[,2]/(1+exp(Z[,1])),
(Z[,1]*Z[,3]/25+0.6)^3,(Z[,2]+Z[,4]+20)^2)
#estimation of natural mediation effecs
fit1<-MED(Y,treat,M,X)
summary(fit1)