msmediate: Causal mediation analysis in multisite trials

In MultisiteMediation: Causal Mediation Analysis in Multisite Trials

Description

This function is used to estimate both the population average and between-site variance of direct and indirect effects.

Usage

msmediate(data, y, treatment, mediator, X, site)

Arguments

data	The data set for analysis.
y	The name of the outcome variable (string).
treatment	The name of the treatment variable (string).
mediator	The name of the mediator variable (string).
X	A vector of variable names (string) of pretreatment covariates, which will be included in the propensity score model. For now, the multilevel propensity score model only allows for one random intercept.
site	The variable name for the site ID (string).

Value

A list contains the estimates of the between-site variance of direct effect, that of indirect effect, and the correlation between the direct and indirect effects across sites ($Random_effects), and the population average direct and indirect effect estimates along with their hypothesis testing results ($Fixed_effects).

Author(s)

Xu Qin and Guanglei Hong

References

Qin, X., & Hong, G (2017). A weighting method for assessing between-site heterogeneity in causal mediation mechanism. Journal of Educational and Behavioral Statistics. Journal of Educational and Behavioral Statistics, 42(3), 308-340. doi: 10.3102/1076998617694879

Examples

data(sim)

msmediate(data = sim, y = "y", treatment = "tr", mediator = "me", X = c("x1", "x2",
    "x3", "x4"), site = "site")

MultisiteMediation documentation built on Sept. 5, 2021, 6:04 p.m.