mediation: summary.ivmediate – R documentation

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summary.ivmediate

Summarizing Output from Mediation Analysis with Treatment Noncompliance

Description

Function to report results from mediation analysis with treatment noncompliance. Reported categories are local average causal mediation effects, local average natural direct effects and local average treatment (total) effect.

Usage

## S3 method for class 'ivmediate'
summary(object, conf.level = object$conf.level[1],
  ...)

## S3 method for class 'summary.ivmediate'
print(x, ...)

Arguments

`object`	output from mediate function.
`conf.level`	confidence level for the intervals reported in the summary table.
`...`	additional arguments affecting the summary produced.
`x`	output from summary.mediate function.

Author(s)

Teppei Yamamoto, Massachusetts Institute of Technology, teppei@mit.edu.

References

Tingley, D., Yamamoto, T., Hirose, K., Imai, K. and Keele, L. (2014). "mediation: R package for Causal Mediation Analysis", Journal of Statistical Software, Vol. 59, No. 5, pp. 1-38.

Yamamoto, T. (2013). Identification and Estimation of Causal Mediation Effects with Treatment Noncompliance. Unpublished manuscript.

Examples

# Examples with JOBS II Field Experiment

# ** For illustration purposes a small number of simulations are used **

require(parallel)
require(MASS)

data(jobs)

a <- lm(comply ~ treat + sex + age + marital + nonwhite + educ + income, 
        data = jobs)
b <- glm(job_dich ~ comply + treat + sex + age + marital + nonwhite + educ + income, 
        data = jobs, family = binomial)
c <- lm(depress2 ~ job_dich * (comply + treat) + sex + age + marital + nonwhite + educ + income, 
        data = jobs)

out <- ivmediate(a, b, c, sims = 50, boot = FALSE,
                 enc = "treat", treat = "comply", mediator = "job_dich")
                 
summary(out)
plot(out)

mediation

Causal Mediation Analysis

v4.5.0

GPL (>= 2)

Authors

Dustin Tingley <dtingley@gov.harvard.edu>, Teppei Yamamoto <teppei@mit.edu>, Kentaro Hirose <hirose@princeton.edu>, Luke Keele <ljk20@psu.edu>, Kosuke Imai <kimai@princeton.edu>, Minh Trinh <mdtrinh@mit.edu>, Weihuang Wong <wwong@mit.edu>

Initial release

2019-9-13