Bootstrap for EM
bmem.em.boot(x, ram, indirect, v, robust = FALSE,
varphi = 0.1, st= "i", boot = 1000,
moment = FALSE, max_it = 500, ...)
Parameter estimates from bootstrap samples
Parameter estimates from the orignal samples
A data set
RAM path for the mediaiton model
A vector of indirect effec
Indices of variables used in the mediation model. If omitted, all variables are used.
Roubst method
Percent of data to be downweighted
Starting values
Number of bootstraps. Default is 1000.
Select mean structure or covariance analysis. moment=FALSE, covariance analysis. moment=TRUE, mean and covariance analysis.
Maximum number of iterations in EM
Other options for sem function can be used.
Zhiyong Zhang and Lijuan Wang
The indirect effect can be specified using equations such as a*b, a*b+c, and a*b*c+d*e+f. A vector of indirect effects can be used indirect=c('a*b', 'a*b+c').