bmem.em.boot: Bootstrap for EM

In johnnyzhz/bmem: Mediation Analysis with Missing Data Using Bootstrap

Bootstrap for EM

Description

Bootstrap for EM

Usage

bmem.em.boot(x, ram, v, robust = FALSE, 
             varphi = 0.1, st= "i", boot = 1000, 
             max_it = 500, parallel=FALSE, ncore=1,...)

Arguments

x	A data set
ram	RAM path for the mediaiton model
v	Indices of variables used in the mediation model. If omitted, all variables are used.
robust	Roubst method
varphi	Percent of data to be downweighted
st	Starting values
boot	Number of bootstraps. Default is 1000.
max_it	Maximum number of iterations in EM
parallel	Whether to use parallel method to calculate.
ncore	Numbers of core for parallel method.
...	Other options for sem function can be used.

Details

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').

Value

par.boot	Parameter estimates from bootstrap samples
par0	Parameter estimates from the orignal samples

Author(s)

Zhiyong Zhang and Lijuan Wang

johnnyzhz/bmem documentation built on Dec. 30, 2022, 8:41 p.m.