vartest.msmediate: Variance testing for multisite causal mediation analysis

In MultisiteMediation: Causal Mediation Analysis in Multisite Trials

Description

This function performs hypothesis testing for the between-site variance of direct effect and that of indirect effect, besides providing the same output as given by the function msmediate().

Usage

vartest.msmediate(data, y, treatment, mediator, X, site, npermute = 200)

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).
npermute	The number of permutations for the permutation test. The default value is 200. It may take a long time, depending on the sample size and the length of X.

Value

A list contains the hypothesis testing results of the between-site variance of the causal effects, besides the same output as given by the function msmediate().

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. Journal of Educational and Behavioral Statistics, 42(3), 308-340. doi: 10.3102/1076998617694879

Examples

data(sim)

vartest.msmediate(data = sim, y = "y", treatment = "tr", mediator = "me", X = c("x1",
    "x2", "x3", "x4"), site = "site", npermute = 2)

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